17.1.3.7.8 Human Safety, Drowning, Underwater, Home Care, Smart Home

Chapter Contents (Back)
Activity Recognition. Human Safety. Home Care. Smart Home.
See also Tracking Animals, Animal Gait, Animal Behaviors.
See also Human Safety, Falling, Fall Detection, Home Care, Smart Home. Relevant papers moved to:
See also Unattended Package, Abandoned Luggage, Left Luggage, Theft.
See also Rehabilitation Systems, Rehabilitation Techniques.

Poseidon Technologies,
1995.
HTML Version. Vendor, Surveillance. Swimmer monitoring. The system saves lives. A part of MG International which has non-vision swimming pool technologies.

Karayiannis, N.B., Srinivasan, S., Bhattacharya, R., Wise, M.S., Frost, J.D., Mizrahi, E.M.,
Extraction of motion strength and motor activity signals from video recordings of neonatal seizures,
MedImg(20), No. 9, September 2001, pp. 965-980.
IEEE Top Reference. 0110
BibRef

Karayiannis, N.B., Varughese, B., Tao, G., Frost, J.D., Wise, M.S., Mizrahi, E.M.,
Quantifying Motion in Video Recordings of Neonatal Seizures by Regularized Optical Flow Methods,
IP(14), No. 7, July 2005, pp. 890-903.
IEEE DOI 0506
BibRef

Karayiannis, N.B.[Nicolaos B.], Tao, G.Z.[Guo-Zhi],
An improved procedure for the extraction of temporal motion strength signals from video recordings of neonatal seizures,
IVC(24), No. 1, 1 January 2006, pp. 27-40.
Elsevier DOI 0602
BibRef
Earlier:
Improving the extraction of temporal motion strength signals from video recordings of neonatal seizures,
AVSBS03(87-92).
IEEE DOI 0310
BibRef

Karayiannis, N.B., Sami, A.,
Application of adaptive block matching in the extraction of temporal motor activity signals from video recordings of neonatal seizures,
AVSBS03(93-98).
IEEE DOI 0310
BibRef

Lu, W.M.[Wen-Miao], Tan, Y.P.[Yap-Peng],
A Vision-Based Approach to Early Detection of Drowning Incidents in Swimming Pools,
CirSysVideo(14), No. 2, February 2004, pp. 159-178.
IEEE Abstract. 0403
BibRef
Earlier:
A camera-based system for early detection of drowning incidents,
ICIP02(III: 445-448).
IEEE DOI 0210
BibRef

Kam, A.H., Lu, W., Yau, W.Y.,
A Video-Based Drowning Detection System,
ECCV02(IV: 297 ff.).
Springer DOI 0205
BibRef

Aubert, D.[Didier], Guichard, F.[Frédéric], Bouchafa, S.[Samia],
Time-scale change detection applied to real-time abnormal stationarity monitoring,
RealTimeImg(10), No. 1, February 2004, pp. 9-22.
Elsevier DOI 0405
Develop a change detection algorithm. Use change detection over time to find non-changes (i.e. people). Used in drowning detection system. BibRef

Meniere, J.[Jerome], Lefebure, M.[Martin], Guichard, F.[Frederic], Migliorini, C.[Christophe],
Method, system and device for detecting an object proximate to a water/air type interface,
US_Patent7,362,351, Apr 22, 2008
WWW Link. BibRef 0804

Guicard, F., Lavest, J.M., Liege, B., Meniere, J.,
Poseidon Technologies: The world's first and only computer-aided drowning detection system,
CVPR01(Demos 17-18). 0110

See also Poseidon Technologies. BibRef

Eng, H.L.[How-Lung], Wang, J.X.[Jun-Xian], Wah, A.H.K.S.[Alvin Harvey Kam Siew], Yau, W.Y.[Wei-Yun],
Robust Human Detection Within a Highly Dynamic Aquatic Environment in Real Time,
IP(15), No. 6, June 2006, pp. 1583-1600.
IEEE DOI 0606
BibRef
Earlier:
Novel region-based modeling for human detection within highly dynamic aquatic environment,
CVPR04(II: 390-397).
IEEE DOI 0408
BibRef

Eng, H.L.[How-Lung], Kam, A.H., Wang, J.X.[Jun-Xian], Yau, W.Y.[Wei-Yun], Jiang, L.J.[Li-Juan],
Human detection and tracking within hostile aquatic environments,
CIAP03(133-138).
IEEE DOI 0310
BibRef

Wang, J.X.[Jun-Xian], Eng, H.L.[How-Lung], Kam, A.H.[Alvin H.], Yau, W.Y.[Wei-Yun],
Specular Reflection Removal for Human Detection under Aquatic Environment,
OTCBVS04(130).
IEEE DOI 0502
BibRef

Eng, H.L.[How-Lung], Wang, J.X.[Jun-Xian], Kam, A.H., Yau, W.Y.[Wei-Yun],
A bayesian framework for robust human detection and occlusion handling using human shape model,
ICPR04(II: 257-260).
IEEE DOI 0409
BibRef

Eng, H.L.[How-Lung], Toh, K.A.[Kar-Ann], Wah, A.H.K.S.[Alvin Harvey Kam Siew], Wang, J.X.[Jun-Xian], Yau, W.Y.[Wei-Yun],
An automatic drowning detection surveillance system for challenging outdoor pool environments,
ICCV03(532-539).
IEEE DOI 0311
BibRef

Eng, H.L.[How-Lung], Toh, K.A.[Kar-Ann], Yau, W.Y.[Wei-Yun], Chiew, T.K.[Tuan-Kiang],
Recognition of Complex Human Behaviors in Pool Environment Using Foreground Silhouette,
ISVC05(371-379).
Springer DOI 0512
BibRef

Eng, H.L., Toh, K.A., Yau, W.Y., Wang, J.,
DEWS: A Live Visual Surveillance System for Early Drowning Detection at Pool,
CirSysVideo(18), No. 2, February 2008, pp. 196-210.
IEEE DOI 0803
BibRef

Juang, C.F., Chang, C.M.,
Human Body Posture Classification by a Neural Fuzzy Network and Home Care System Application,
SMC-A(37), No. 6, November 2007, pp. 984-994.
IEEE DOI 0709
BibRef

Juang, C.F., Chang, C.M., Wu, J.R., Lee, D.,
Computer Vision-Based Human Body Segmentation and Posture Estimation,
SMC-A(39), No. 1, January 2009, pp. 119-133.
IEEE DOI 0901
BibRef

Yang, J.H.[Jeong-Hwa], Schilit, B.N.[Bill N.], McDonald, D.W.[David W.],
Activity Recognition for the Digital Home,
Computer(41), No. 4, April 2008, pp. 102-104.
IEEE DOI 0804
BibRef

Want, R.[Roy], Schilit, B.N.[Bill N.],
Interactive Digital Signage,
Computer(45), No. 5, May 2012, pp. 21-24.
IEEE DOI 1202
BibRef

Chung, P.C.[Pau-Choo], Liu, C.D.[Chin-De],
A daily behavior enabled hidden Markov model for human behavior understanding,
PR(41), No. 5, May 2008, pp. 1589-1597.
Elsevier DOI 0711
Behavior recognition; Duration HMM; Hierarchical HMM; Context BibRef

Snoek, J.[Jasper], Hoey, J.[Jesse], Stewart, L.[Liam], Zemel, R.S.[Richard S.], Mihailidis, A.[Alex],
Automated Detection of Unusual Events on Stairs,
IVC(27), No. 1-2, January 2009, pp. 153-166.
Elsevier DOI 0811
BibRef
Earlier: A1, A2, A3, A4, Only: CRV06(5-5).
IEEE DOI 0607
Human motion analysis; Hidden Markov model; Gait analysis; Anomaly detection; Event recognition; Bayesian tracking; Particle filter; Automated video analysis; Machine learning; Biomedical analysis; Stairs BibRef

Hoey, J.[Jesse], Poupart, P.[Pascal], von Bertoldi, A.[Axel], Craig, T.[Tammy], Boutilier, C.[Craig], Mihailidis, A.[Alex],
Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process,
CVIU(114), No. 5, May 2010, pp. 503-519.
Elsevier DOI 1004
Assistive technology; Decision theory; Human tracking; Particle filters; Behavior monitoring; POMDP; User trials BibRef

Jeong, I.W.[Il-Woong], Choi, J.[Jin], Cho, K.[Kyusung], Seo, Y.H.[Yong-Ho], Yang, H.S.[Hyun Seung],
A Vision-Based Emergency Response System with a Paramedic Mobile Robot,
IEICE(E93-D), No. 7, July 2010, pp. 1745-1753.
WWW Link. 1008
Surveillance for elderly. BibRef

GE Healthcare's Smart Patient Room to Begin Data Collection,
GE Healthcarepress release, September 2010.
WWW Link. Vision included in patient monitoring. BibRef 1009

Ahmad, M.[Mohiuddin], Lee, S.W.[Seong-Whan],
Human action recognition using shape and CLG-motion flow from multi-view image sequences,
PR(41), No. 7, July 2008, pp. 2237-2252.
Elsevier DOI 0804
BibRef
And:
Recognizing human actions based on silhouette energy image and global motion description,
FG08(1-6).
IEEE DOI 0809
BibRef
Earlier:
HMM-based Human Action Recognition Using Multiview Image Sequences,
ICPR06(I: 263-266).
IEEE DOI 0609
BibRef
And:
Human Action Recognition Using Multi-View Image Sequences Features,
FGR06(523-528).
IEEE DOI 0604
Action recognition; Action matrix; Combined local-global (CLG) optic flow; Invariant Zernike moments; Multi-view image sequence; Multidimensional hidden Markov model (MDHMM) BibRef

Ahmad, M.[Mohiuddin], Lee, S.W.[Seong-Whan],
Variable silhouette energy image representations for recognizing human actions,
IVC(28), No. 5, May 2010, pp. 814-824.
Elsevier DOI 1003
Silhouette energy image; Action recognition; Variability action models; Daily life actions; Global motion description BibRef

Gualdi, G.[Giovanni], Prati, A.[Andrea], Cucchiara, R.[Rita],
Contextual Information and Covariance Descriptors for People Surveillance: An Application for Safety of Construction Workers,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link 1101

See also Multi-stage Sampling with Boosting Cascades for Pedestrian Detection in Images and Videos. BibRef

Chung, P.C.[Pau-Choo], Kuo, Y.M.[Yung-Ming], Liu, C.D.[Chin-De], Huang, C.R.[Chun-Rong],
Video analysis boosts healthcare efficiency and safety,
SPIE(Newsroom), February 10, 2011.
DOI Link 1102
Video-pattern-recognition programs enable automated patient monitoring for diagnostic and safety purposes, thus reducing staffing requirements in hospitals and nursing homes. BibRef

Grabowski, A., Kosinski, R.A., Dzwiarek, M.,
Vision safety system based on cellular neural networks,
MVA(22), No. 3, May 2011, pp. 581-590.
WWW Link. 1104
Human-machine interface where there is spatial overlap. Detect when human is in danger. BibRef

San Miguel, J.C.[Juan Carlos], Martínez, J.M.[José M.],
Use of feedback strategies in the detection of events for video surveillance,
IET-CV(5), No. 5, 2011, pp. 309-319.
DOI Link 1110
BibRef
Earlier:
Robust Unattended and Stolen Object Detection by Fusing Simple Algorithms,
AVSBS08(18-25).
IEEE DOI 0809

See also Commentary Paper 2 on Robust Unattended and Stolen Object Detection by Fusing Simple Algorithms.
See also Commentary Paper 1 on Robust Unattended and Stolen Object Detection by Fusing Simple Algorithms. BibRef

Wang, C.W.[Ching-Wei], Hunter, A.[Andrew],
Robust Pose Recognition of the Obscured Human Body,
IJCV(90), No. 3, December 2010, pp. 313-330.
WWW Link. 1011
BibRef
And: Erratum: IJCV(94), No. 3, September 2011, pp. 375.
WWW Link. 1101
Compare to:
See also Tracking People by Learning Their Appearance. Use for sleeping human and pedestrians with clutter. BibRef

Alam, M.R., Reaz, M.B.I., Mohd Ali, M. A.,
SPEED: An Inhabitant Activity Prediction Algorithm for Smart Homes,
SMC-A(42), No. 4, July 2012, pp. 985-990.
IEEE DOI 1206
BibRef

Beetz, M., Jain, D., Mosenlechner, L., Tenorth, M., Kunze, L., Blodow, N., Pangercic, D.,
Cognition-Enabled Autonomous Robot Control for the Realization of Home Chore Task Intelligence,
PIEEE(100), No. 8, August 2012, pp. 2454-2471.
IEEE DOI 1208
BibRef

Ramirez-Amaro, K.[Karinne], Beetz, M.[Michael], Cheng, G.[Gordon],
Transferring skills to humanoid robots by extracting semantic representations from observations of human activities,
AI(247), No. 1, 2017, pp. 95-118.
Elsevier DOI 1705
Activity, recognition BibRef

Helal, S., Chen, C., Kim, E., Bose, R., Lee, C.,
Toward an Ecosystem for Developing and Programming Assistive Environments,
PIEEE(100), No. 8, August 2012, pp. 2489-2504.
IEEE DOI 1208
BibRef

Wang, F.[Fei], Lee, N.[Noah], Hu, J.Y.[Jian-Ying], Sun, J.[Jimeng], Ebadollahi, S.[Shahram], Laine, A.F.[Andrew F.],
A Framework for Mining Signatures from Event Sequences and Its Applications in Healthcare Data,
PAMI(35), No. 2, February 2013, pp. 272-285.
IEEE DOI 1301
Events, not visual data. Electronic health records. BibRef

Chan, K.L.,
Detection of swimmer using dense optical flow motion map and intensity information,
MVA(24), No. 1, January 2013, pp. 75-101.
WWW Link. 1301

See also Video-based Gait Analysis By Silhouette Chamfer Distance And Kalman Filter. BibRef

Forsyth, D.A.[David A.],
Technical Perspective: Understanding Pictures of Rooms,
CACM(56), No. 4, April 2013, pp. 91.
DOI Link 1304
The rich world is getting older, so we will see many efforts to build robots that can provide some in-home care for frail people. These robots will need computer programs that can see and understand rooms where people live BibRef

Cook, D.J., Krishnan, N.C., Rashidi, P.,
Activity Discovery and Activity Recognition: A New Partnership,
Cyber(43), No. 3, 2013, pp. 820-828.
IEEE DOI 1307
home automation; behavioral pattern identification; Smart homes; Activity recognition BibRef

Lu, C.H., Ho, Y.C., Chen, Y.H., Fu, L.C.,
Hybrid User-Assisted Incremental Model Adaptation for Activity Recognition in a Dynamic Smart-Home Environment,
HMS(43), No. 5, 2013, pp. 421-436.
IEEE DOI 1311
Active learning BibRef

Dawadi, P.N., Cook, D.J., Schmitter-Edgecombe, M.,
Automated Cognitive Health Assessment Using Smart Home Monitoring of Complex Tasks,
SMCS(43), No. 6, 2013, pp. 1302-1313.
IEEE DOI 1311
Dementia BibRef

Chen, B.W., Chen, C.Y., Wang, J.F.,
Smart Homecare Surveillance System: Behavior Identification Based on State-Transition Support Vector Machines and Sound Directivity Pattern Analysis,
SMCS(43), No. 6, 2013, pp. 1279-1289.
IEEE DOI 1311
Ambient intelligence BibRef

Magherini, T., Fantechi, A., Nugent, C.D., Vicario, E.,
Using Temporal Logic and Model Checking in Automated Recognition of Human Activities for Ambient-Assisted Living,
HMS(43), No. 6, 2013, pp. 509-521.
IEEE DOI 1312
Assisted living BibRef

Biagi, M., Carnevali, L., Paolieri, M., Patara, F., Vicario, E.,
A Continuous-Time Model-Based Approach for Activity Recognition in Pervasive Environments,
HMS(49), No. 4, August 2019, pp. 293-303.
IEEE DOI 1908
Hidden Markov models, Stochastic processes, Ambient assisted living, Transient analysis, Data models, transient analysis BibRef

Zhang, X.P.[Xin-Peng], Yamada, Y.[Yusuke], Kato, T.[Takekazu], Matsuyama, T.[Takashi],
A Novel Method for the Bi-directional Transformation between Human Living Activities and Appliance Power Consumption Patterns,
IEICE(E97-D), No. 2, February 2013, pp. 275-284.
WWW Link. 1402
BibRef

Spampinato, C.[Concetto], Beauxis-Aussalet, E.[Emmanuelle], Palazzo, S.[Simone], Beyan, C.[Cigdem], van Ossenbruggen, J.[Jacco], He, J.[Jiyin], Boom, B.J.[Bas J.], Huang, X.[Xuan],
A rule-based event detection system for real-life underwater domain,
MVA(25), No. 1, January 2014, pp. 99-117.
Springer DOI 1402
BibRef

Chen, L.M.[Li-Ming], Nugent, C., Okeyo, G.,
An Ontology-Based Hybrid Approach to Activity Modeling for Smart Homes,
HMS(44), No. 1, February 2014, pp. 92-105.
IEEE DOI 1403
assisted living BibRef

Ntonfo, G.M.K.[Guy Mathurin Kouamou],
Monitoring and Diagnosing Neonatal Seizures by Video Signal Processing,
ELCVIA(13), No. 2, 2014, pp. xx-yy.
DOI Link 1407
Ph.D.. Thesis. BibRef

Mone, G.[Gregory],
Intelligent Living,
CACM(57), No. 12, December 2014, pp. 15-16.
DOI Link 1412
Smart Rooms BibRef

Forkan, A.R.M.[Abdur Rahim Mohammad], Khalil, I.[Ibrahim], Tari, Z.[Zahir], Foufou, S.[Sebti], Bouras, A.[Abdelaziz],
A context-aware approach for long-term behavioural change detection and abnormality prediction in ambient assisted living,
PR(48), No. 3, 2015, pp. 628-641.
Elsevier DOI 1412
Context-aware BibRef

Deboeverie, F.[Francis], Kleihorst, R.[Richard], Philips, W.[Wilfried], Hanca, J.[Jan], Munteanu, A.[Adrian],
A low-cost visual sensor network for elderly care,
SPIE(Newsroom), December 23, 2014.
DOI Link 1501
A low-resolution visual sensor network enables monitoring of elderly people's health and safety at home, postponing institutionalized healthcare. BibRef

Hanca, J.[Jan], Braeckman, G.[Geert], Munteanu, A.[Adrian], Philips, W.[Wilfried],
Lightweight real-time error-resilient encoding of visual sensor data,
RealTimeIP(12), No. 4, December 2016, pp. 775-789.
Springer DOI 1612
BibRef

Vlasenko, I., Nikolaidis, I., Stroulia, E.,
The Smart-Condo: Optimizing Sensor Placement for Indoor Localization,
SMCS(45), No. 3, March 2015, pp. 436-453.
IEEE DOI 1502
Accuracy BibRef

Jain, R.C.[Ramesh C.], Jalali, L.[Laleh],
Objective Self,
MultMedMag(21), No. 4, October 2014, pp. 100-110.
IEEE DOI 1502
healthcare monitoring BibRef

Jalali, L.[Laleh], Oh, H.[Hyungik], Moazeni, R.[Ramin], Jain, R.C.[Ramesh C.],
Human Behavior Analysis from Smartphone Data Streams,
HBU16(68-85).
Springer DOI 1611
BibRef

Rosani, A.[Andrea], Boato, G.[Giulia], de Natale, F.G.B.[Francesco G.B.],
EventMask: A Game-Based Framework for Event-Saliency Identification in Images,
MultMed(17), No. 8, August 2015, pp. 1359-1371.
IEEE DOI 1506
Context BibRef

Lee, Y.J.[Yu-Ju], Huang, M.C.[Ming-Chun], Zhang, X.Y.[Xiao-Yi], Xu, W.[Wenyao],
FridgeNet: A Nutrition and Social Activity Promotion Platform for Aging Populations,
IEEE_Int_Sys(30), No. 4, July 2015, pp. 23-30.
IEEE DOI 1506
Aging BibRef

Mangano, S.[Simone], Saidinejad, H.[Hassan], Veronese, F.[Fabio], Comai, S.[Sara], Matteucci, M.[Matteo], Salice, F.[Fabio],
Bridge: Mutual Reassurance for Autonomous and Independent Living,
IEEE_Int_Sys(30), No. 4, July 2015, pp. 31-38.
IEEE DOI 1506
Active appearance model BibRef

Lee, E.,
Wearables for frail seniors,
Spectrum(52), No. 9, September 2015, pp. 25-25.
IEEE DOI 1509
Resources_Tools. BibRef

Zhang, H., Zhou, W., Parker, L.E.,
Fuzzy Temporal Segmentation and Probabilistic Recognition of Continuous Human Daily Activities,
HMS(45), No. 5, October 2015, pp. 598-611.
IEEE DOI 1509
Clustering algorithms BibRef

Lee, D., Helal, A.S., Sung, Y., Anton, S.,
Situation-Based Assess Tree for User Behavior Assessment in Persuasive Telehealth,
HMS(45), No. 5, October 2015, pp. 624-634.
IEEE DOI 1509
Context BibRef

Banerjee, T.[Tanvi], Keller, J.M.[James M.], Popescu, M.[Mihail], Skubic, M.[Marjorie],
Recognizing complex instrumental activities of daily living using scene information and fuzzy logic,
CVIU(140), No. 1, 2015, pp. 68-82.
Elsevier DOI 1509
Scene understanding BibRef

Iocchi, L.[Luca], Holz, D.[Dirk], Ruiz-del-Solar, J.[Javier], Sugiura, K.[Komei], van der Zant, T.[Tijn],
RoboCup@Home: Analysis and results of evolving competitions for domestic and service robots,
AI(229), No. 1, 2015, pp. 258-281.
Elsevier DOI 1511
Robotic competitions BibRef

Wan, J., Byrne, C.A., OGrady, M.J., OHare, G.M.P.,
Managing Wandering Risk in People With Dementia,
HMS(45), No. 6, December 2015, pp. 819-823.
IEEE DOI 1512
Ambient assisted living BibRef

Saunders, J., Syrdal, D.S., Koay, K.L.[Kheng Lee], Burke, N., Dautenhahn, K.,
'Teach Me-Show Me' End-User Personalization of a Smart Home and Companion Robot,
HMS(46), No. 1, February 2016, pp. 27-40.
IEEE DOI 1602
geriatrics BibRef

Nguyen, T.[Thuong], Gupta, S.I.[Sun-Il], Venkatesh, S.[Svetha], Phung, D.Q.[Dinh Q.],
Nonparametric discovery of movement patterns from accelerometer signals,
PRL(70), No. 1, 2016, pp. 52-58.
Elsevier DOI 1602
Movement intensity. Monitoring daily physical activity. BibRef

Nguyen, T.B.[Thanh-Binh], Nguyen, V.[Vu], Venkatesh, S.[Svetha], Phung, D.[Dinh],
MCNC: Multi-Channel Nonparametric Clustering from heterogeneous data,
ICPR16(3633-3638)
IEEE DOI 1705
Bayes methods, Computational modeling, Context, Context modeling, Data mining, Data models, Indexes, Bayesian nonparametrics, MCNC, clustering, heterogeneous data, product-space, ubiquitous, computing BibRef

Ahmad, F., Cetin, A.E., Ho, K.C.D.[K. C. D.], Nelson, J.,
Signal Processing for Assisted Living: Developments and Open Problems,
SPMag(33), No. 2, March 2016, pp. 25-26.
IEEE DOI 1603
Intro From the Guest Editors. Assisted living BibRef

Bennett, T.R., Wu, J., Kehtarnavaz, N., Jafari, R.,
Inertial Measurement Unit-Based Wearable Computers for Assisted Living Applications: A signal processing perspective,
SPMag(33), No. 2, March 2016, pp. 28-35.
IEEE DOI 1603
Assisted living BibRef

Erden, F., Velipasalar, S., Alkar, A.Z., Cetin, A.E.,
Sensors in Assisted Living: A survey of signal and image processing methods,
SPMag(33), No. 2, March 2016, pp. 36-44.
IEEE DOI 1603
BibRef

Savazzi, S., Sigg, S., Nicoli, M., Rampa, V., Kianoush, S., Spagnolini, U.,
Device-Free Radio Vision for Assisted Living: Leveraging wireless channel quality information for human sensing,
SPMag(33), No. 2, March 2016, pp. 45-58.
IEEE DOI 1603
Assisted living BibRef

Witrisal, K., Meissner, P., Leitinger, E., Shen, Y., Gustafson, C., Tufvesson, F., Haneda, K., Dardari, D., Molisch, A.F., Conti, A., Win, M.Z.,
High-Accuracy Localization for Assisted Living: 5G systems will turn multipath channels from foe to friend,
SPMag(33), No. 2, March 2016, pp. 59-70.
IEEE DOI 1603
Assisted living BibRef

Debes, C., Merentitis, A., Sukhanov, S., Niessen, M., Frangiadakis, N., Bauer, A.,
Monitoring Activities of Daily Living in Smart Homes: Understanding human behavior,
SPMag(33), No. 2, March 2016, pp. 81-94.
IEEE DOI 1603
Accelerometers BibRef

Yun, Y.X.[Yi-Xiao], Gu, I.Y.H.[Irene Yu-Hua],
Riemannian manifold-valued part-based features and geodesic-induced kernel machine for activity classification dedicated to assisted living,
CVIU(161), No. 1, 2017, pp. 65-76.
Elsevier DOI 1708
Activity of daily living. BibRef

Andreu, Y.[Yasmina], Chiarugi, F.[Franco], Colantonio, S.[Sara], Giannakakis, G.[Giorgos], Giorgi, D.[Daniela], Henriquez, P.[Pedro], Kazantzaki, E.[Eleni], Manousos, D.[Dimitris], Marias, K.[Kostas], Matuszewski, B.J.[Bogdan J.], Pascali, M.A.[Maria Antonietta], Pediaditis, M.[Matthew], Raccichini, G.[Giovanni], Tsiknakis, M.[Manolis],
Wize Mirror: A smart, multisensory cardio-metabolic risk monitoring system,
CVIU(148), No. 1, 2016, pp. 3-22.
Elsevier DOI 1606
Unobtrusive health monitoring BibRef

Marcon, M.[Marco], Sarti, A.[Augusto], Tubaro, S.[Stefano],
Toothbrush motion analysis to help children learn proper tooth brushing,
CVIU(148), No. 1, 2016, pp. 34-45.
Elsevier DOI 1606
BibRef
And:
Smart Toothbrushes: Inertial Measurement Sensors Fusion with Visual Tracking,
ACVR16(II: 480-494).
Springer DOI 1611
Target tracking BibRef

Park, M.H.[Myong-Hwa],
Usability test of game-based learning in safe-medication education for older adults,
IJCVR(6), No. 3, 2016, pp. 261-266.
DOI Link 1608
BibRef

Nejati, H., Pomponiu, V., Do, T.T., Zhou, Y., Iravani, S., Cheung, N.M.,
Smartphone and Mobile Image Processing for Assisted Living: Health-monitoring apps powered by advanced mobile imaging algorithms,
SPMag(33), No. 4, July 2016, pp. 30-48.
IEEE DOI 1608
assisted living BibRef

Jaimes, L.G., Llofriu, M., Raij, A.,
PREVENTER, a Selection Mechanism for Just-in-Time Preventive Interventions,
AffCom(7), No. 3, July 2016, pp. 243-257.
IEEE DOI 1609
Biological system modeling BibRef

Liu, L.[Li], Wang, S.[Shu], Peng, Y.X.[Yu-Xin], Huang, Z.[Zigang], Liu, M.[Ming], Hu, B.[Bin],
Mining intricate temporal rules for recognizing complex activities of daily living under uncertainty,
PR(60), No. 1, 2016, pp. 1015-1028.
Elsevier DOI 1609
Complex activity recognition BibRef

Cattani, L.[Luca],
Monitoring Infants by Automatic Video Processing,
ELCVIA(15), No. 2, 2016, pp. 10-12.
DOI Link 1611
BibRef

Sprint, G., Cook, D.J., Fritz, R., Schmitter-Edgecombe, M.,
Using Smart Homes to Detect and Analyze Health Events,
Computer(49), No. 11, November 2016, pp. 29-37.
IEEE DOI 1612
assisted living BibRef

Wahl, F., Zhang, R., Freund, M., Amft, O.,
Personalizing 3D-Printed Smart Eyeglasses to Augment Daily Life,
Computer(50), No. 2, February 2017, pp. 26-35.
IEEE DOI 1702
Biomedical monitoring BibRef

Jukan, A.[Admela], Masip-Bruin, X.[Xavi], Amla, N.[Nina],
Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review,
Surveys(50), No. 1, April 2017, pp. Article No 10.
DOI Link 1704
Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but now they work to assist the disabled, and in combat and search and rescue situations. BibRef

Rafferty, J., Nugent, C.D., Liu, J., Chen, L.,
From Activity Recognition to Intention Recognition for Assisted Living Within Smart Homes,
HMS(47), No. 3, June 2017, pp. 368-379.
IEEE DOI 1706
Activity recognition, Aging, Hidden Markov models, Intelligent agents, Intelligent sensors, Smart homes, Activity recognition, ambient-assisted living (AAL), goal recognition, intelligent agents, intention recognition (IR), smart homes, (SHs) BibRef

Chiang, Y.T., Lu, C.H., Hsu, J.Y.J.,
A Feature-Based Knowledge Transfer Framework for Cross-Environment Activity Recognition Toward Smart Home Applications,
HMS(47), No. 3, June 2017, pp. 310-322.
IEEE DOI 1706
Data models, Feature extraction, Knowledge transfer, Sensor phenomena and characterization, Smart homes, Testing, Activity recognition (AR), feature-based knowledge transfer framework, smart home, transfer, learning BibRef

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Mirror Mirror on the Wall... An Unobtrusive Intelligent Multisensory Mirror for Well-Being Status Self-Assessment and Visualization,
MultMed(19), No. 7, July 2017, pp. 1467-1481.
IEEE DOI 1706
Cameras, Face, Face detection, Mirrors, Sensors, Videos, Solid modeling, 3D face detection and tracking, 3D morphometric analysis, Cardio-metabolic risk, breath analysis, multimodal data integration, multispectral imaging, psychosomatic status recognition, unobtrusive, well-being, monitoring BibRef

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Wearable computing for railway environments: proposal and evaluation of a safety solution,
IET-ITS(11), No. 6, August 2017, pp. 319-325.
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IJGI(6), No. 10, 2017, pp. xx-yy.
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Active and Assisted Living. Where user stays and how long. BibRef

Batalla, J.M.[Jordi Mongay], Vasilakos, A.[Athanasios], Gajewski, M.[Mariusz],
Secure Smart Homes: Opportunities and Challenges,
Surveys(50), No. 5, November 2017, pp. Article No 75.
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Survey, Smart Homes. Sensors, security, future. BibRef

Gao, Z., Guo, H., Xie, Y., Luo, Y., Lu, H., Yan, K.,
ChildGuard: A Child-Safety Monitoring System,
MultMedMag(24), No. 4, October 2017, pp. 48-57.
IEEE DOI 1712
China, Computer security, Mobile handsets, Pediatrics, Privacy, Real-time systems, Safety, Video surveillance, Web servers, ubiquitous security BibRef

Ma, R., Hu, F., Hao, Q.,
Active Compressive Sensing via Pyroelectric Infrared Sensor for Human Situation Recognition,
SMCS(47), No. 12, December 2017, pp. 3340-3350.
IEEE DOI 1712
Cameras, Choppers (circuits), Magnetic sensors, Sensor systems, Thermal sensors, Wearable sensors, Active sensing, situation recognition BibRef

Booth, K.E.C., Mohamed, S.C., Rajaratnam, S., Nejat, G., Beck, J.C.,
Robots in Retirement Homes: Person Search and Task Planning for a Group of Residents by a Team of Assistive Robots,
IEEE_Int_Sys(32), No. 6, November 2017, pp. 14-21.
IEEE DOI 1801
Databases, Games, Retirement, Robot sensing systems, Schedules, Task analysis, constraint satisfaction, intelligent systems, user/machine systems BibRef

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Robots Understanding Contextual Information in Human-Centered Environments Using Weakly Supervised Mask Data Distillation,
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Springer DOI 2301
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Fanti, M.P., Faraut, G., Lesage, J.J., Roccotelli, M.,
An Integrated Framework for Binary Sensor Placement and Inhabitants Location Tracking,
SMCS(48), No. 1, January 2018, pp. 154-160.
IEEE DOI 1801
assisted living, data privacy, integer programming, linear programming, sensor placement, wireless sensor networks, smart home BibRef

Hbali, Y.[Youssef], Hbali, S.[Sara], Ballihi, L.[Lahoucine], Sadgal, M.[Mohammed],
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IET-CV(12), No. 1, February 2018, pp. 16-26.
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Zhang, J., Wang, Y., Wang, C., Zhou, M.,
Fast Variable Structure Stochastic Automaton for Discovering and Tracking Spatiotemporal Event Patterns,
Cyber(48), No. 3, March 2018, pp. 890-903.
IEEE DOI 1802
Ambient assisted living, Automata, Convergence, Learning automata, Noise measurement, Pattern recognition, Spatiotemporal phenomena, spatiotemporal event pattern BibRef

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PRL(105), 2018, pp. 135-143.
Elsevier DOI 1804
Parkinson's disease, Triaxial accelerometer, Machine learning, Feature reduction, Freezing of gait BibRef

Robillard, J.M., Hoey, J.,
Emotion and Motivation in Cognitive Assistive Technologies for Dementia,
Computer(51), No. 3, March 2018, pp. 24-34.
IEEE DOI 1804
Affective computing, Assistive technology, Cultural differences, Decision making, Dementia, ACT, Affect Control Theory, BayesACT, healthcare BibRef

Khaliluzzaman, M., Deb, K.[Kaushik],
Stairways detection based on approach evaluation and vertical vanishing point,
IJCVR(8), No. 2, 2018, pp. 168-189.
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Springer DOI 1808
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A Survey on Smart Homes for Aging in Place: Toward Solutions to the Specific Needs of the Elderly,
SPMag(35), No. 5, September 2018, pp. 111-119.
IEEE DOI 1809
Survey, Smart Homes. Wearable sensors, Monitoring, Smart homes, Aging, Intelligent sensors, Sensor systems BibRef

Jia, R., Jin, B., Jin, M., Zhou, Y., Konstantakopoulos, I.C., Zou, H., Kim, J., Li, D., Gu, W., Arghandeh, R., Nuzzo, P., Schiavon, S., Sangiovanni-Vincentelli, A.L., Spanos, C.J.,
Design Automation for Smart Building Systems,
PIEEE(106), No. 9, September 2018, pp. 1680-1699.
IEEE DOI 1810
building management systems, buildings (structures), civil engineering computing, cyber-physical systems, smart building BibRef

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A Multiview Multimodal System for Monitoring Patient Sleep,
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IEEE DOI 1810
Multi-stage noise shaping, Hidden Markov models, Medical services, Feature extraction, Monitoring, Cameras, Videos, M.A.S.H BibRef

Machot, F.A., Mosa, A.H., Ali, M., Kyamakya, K.,
Activity Recognition in Sensor Data Streams for Active and Assisted Living Environments,
CirSysVideo(28), No. 10, October 2018, pp. 2933-2945.
IEEE DOI 1811
Activity recognition, Hidden Markov models, Smart homes, Feature extraction, Bayes methods, Convolution, Classification, smart homes BibRef

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PAMI(42), No. 10, October 2020, pp. 2540-2551.
IEEE DOI 2009
Shape, Biological system modeling, Data models, Animals, Face, Avatars, Body models, data-driven, RGB-D, motion analysis BibRef

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Unsupervised human activity analysis for intelligent mobile robots,
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Elsevier DOI 1906
Human activity analysis, Mobile robotics, Qualitative spatio-temporal representation, Latent Dirichlet allocation BibRef

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PRL(137), 2020, pp. 61-70.
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Elderly well-being, Positive technology, Machine learning, Intelligent cognitive assistants, Ambient assisted living BibRef

Sánchez, V.G.[Veralia Gabriela], Lysaker, O.M.[Ola Marius], Skeie, N.O.[Nils-Olav],
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Ambient assisted living, HMM, Behaviour recognition, Assistive technology, Pattern recognition, Norway, Smart house BibRef

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Thermal comfort measurement, Thermal-depth images, Clothing insulation, Mobile assistive robot BibRef

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A projective chirp based stair representation and detection from monocular images and its application for the visually impaired,
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Color-based stair detection, Chirp pattern, Stair modeling BibRef

Miandashti, F.J., Izadi, M., Shirehjini, A.A.N., Shirmohammadi, S.,
An Empirical Approach to Modeling User-System Interaction Conflicts in Smart Homes,
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IEEE DOI 2011
Smart homes, Safety, Human computer interaction, Performance evaluation, Human-robot interaction, smart home conflicts BibRef

Edu, J.S.[Jide S.], Such, J.M.[Jose M.], Suarez-Tangil, G.[Guillermo],
Smart Home Personal Assistants: A Security and Privacy Review,
Surveys(53), No. 6, December 2020, pp. xx-yy.
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Survey, Smart Home. Amazon Echo/Alexa, smart home, voice assistants, Smart home personal assistants, Google Home/assistant, Apple Home Pod/Siri BibRef

Wang, T.H.[Ting-Hui], Cook, D.J.[Diane J.],
sMRT: Multi-Resident Tracking in Smart Homes With Sensor Vectorization,
PAMI(43), No. 8, August 2021, pp. 2809-2821.
IEEE DOI 2107
Smart homes, Layout, Hidden Markov models, Monitoring, Data models, Tracking, Building automation, Smart home, time series, sensor networks BibRef

Rabiee, R.[Ramtin], Karlsson, J.[Johannes],
Multi-Bernoulli Tracking Approach for Occupancy Monitoring of Smart Buildings Using Low-Resolution Infrared Sensor Array,
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Wang, Q.[Qi], Zhang, S.[Senlin], Sheng, W.H.[Wei-Hua], Chen, B.D.[Ba-Dong], Liu, M.Q.[Mei-Qin],
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Service robotics, Incremental learning, Bioinspired robot learning BibRef

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Levels of Automation and Transparency: Interaction Design Considerations in Assistive Robots for Older Adults,
HMS(51), No. 6, December 2021, pp. 673-683.
IEEE DOI 2112
Robots, Task analysis, Automation, Assistive devices, Human-robot interaction, Assistive robots (ARs), socially ARs BibRef

Perez, B.[Beatrice], Mazzaro, G.[Gregory], Pierson, T.J.[Timothy J.], Kotz, D.[David],
Detecting the Presence of Electronic Devices in Smart Homes Using Harmonic Radar Technology,
RS(14), No. 2, 2022, pp. xx-yy.
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Shu, X.B.[Xiang-Bo], Yang, J.[Jiawen], Yan, R.[Rui], Song, Y.[Yan],
Expansion-Squeeze-Excitation Fusion Network for Elderly Activity Recognition,
CirSysVideo(32), No. 8, August 2022, pp. 5281-5292.
IEEE DOI 2208
Older adults, Skeleton, Feature extraction, Fuses, Hair, Videos, Task analysis, Elderly activity recognition, multi-modal fusion BibRef

Cheng, J.[Junyi], Zhang, X.F.[Xian-Feng], Chen, X.[Xiao], Ren, M.[Miao], Huang, J.[Jie], Luo, P.[Peng],
Early Detection of Suspicious Behaviors for Safe Residence from Movement Trajectory Data,
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Liu, S.J.[Shuang-Jun], Huang, X.F.[Xiao-Fei], Fu, N.[Nihang], Li, C.[Cheng], Su, Z.[Zhongnan], Ostadabbas, S.[Sarah],
Simultaneously-Collected Multimodal Lying Pose Dataset: Enabling In-Bed Human Pose Monitoring,
PAMI(45), No. 1, January 2023, pp. 1106-1118.
IEEE DOI 2212
Pose estimation, Monitoring, Imaging, Hospitals, Benchmark testing, Training, Human pose estimation, depth sensing, in-bed poses, thermal imaging BibRef

Chen, K.Q.[Kai-Qi], Liu, J.L.[Jia-Ling], Chen, Q.Y.[Qin-Ying], Wang, Z.H.[Zhen-Hua], Zhang, J.H.[Jian-Hua],
Accurate Object Association and Pose Updating for Semantic SLAM,
ITS(23), No. 12, December 2022, pp. 25169-25179.
IEEE DOI 2212
For hospital robots. Simultaneous localization and mapping, Semantics, Visualization, Robots, Hospitals, Time measurement, Location awareness BibRef

Her, P.[Paris], Manderle, L.[Logan], Dias, P.A.[Philipe A.], Medeiros, H.[Henry], Odone, F.[Francesca],
Uncertainty-Aware Gaze Tracking for Assisted Living Environments,
IP(32), 2023, pp. 2335-2347.
IEEE DOI 2305
Uncertainty, Head, Assisted living, Gaze tracking, Videos, Pose estimation, Neural networks, Machine learning, gaze tracking, multi-camera assisted living scenario BibRef

Huang, C.R.[Chao-Ran], Yao, L.[Lina], Wang, X.Z.[Xian-Zhi], Sheng, Q.Z.[Quan Z.], Dustdar, S.[Schahram], Wang, Z.J.[Zhong-Jie], Xu, X.F.[Xiao-Fei],
Intent-Aware Interactive Internet of Things for Enhanced Collaborative Ambient Intelligence,
Internet(26), No. 5, 2022, pp. 68-75.
IEEE DOI 2305
IoT for smart home. BibRef

Liu, T.Z.[Ting-Zhuang], He, X.Y.[Xin-Yu], He, L.L.[Ling-Lu], Yuan, F.[Fei],
A video drowning detection device based on underwater computer vision,
IET-IPR(17), No. 6, 2023, pp. 1905-1918.
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computer vision, object detection, real-time systems, unsupervised learning BibRef

Yamout, Y.[Youssef], Yeasar, T.S.[Tashaffi Samin], Iqbal, S.[Shahrear], Zulkernine, M.[Mohammad],
Beyond Smart Homes: An In-Depth Analysis of Smart Aging Care System Security,
Surveys(56), No. 2, September 2023, pp. 45.
DOI Link 2310
smart home, IoT, security issues, countermeasures, smart healthcare, Smart aging care system BibRef

Zhao, A.[Aite], Wang, Y.[Yue], Li, J.B.[Jian-Bo],
Transferable Self-Supervised Instance Learning for Sleep Recognition,
MultMed(25), 2023, pp. 4464-4477.
IEEE DOI 2310
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Zhang, Y.J.[Yi-Jian], Tao, Q.Y.[Qian-Yi], Yin, Y.[Yong],
A Lightweight Man-Overboard Detection and Tracking Model Using Aerial Images for Maritime Search and Rescue,
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Jokar, F.[Fatemeh], Azzopardi, G.[George], Palotti, J.[Joao],
Towards Accurate and Efficient Sleep Period Detection Using Wearable Devices,
CAIP23(II:43-54).
Springer DOI 2312
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Poudel, R.[Rajeev], Lima, L.[Luciano], Andrade, F.[Fabio],
A Novel Framework to Evaluate and Train Object Detection Models for Real-Time Victims Search and Rescue at Sea with Autonomous Unmanned Aerial Systems Using High-Fidelity Dynamic Marine Simulation Environment,
Maritime23(239-247)
IEEE DOI 2302
Training, Atmospheric modeling, Computational modeling, Brightness, Object detection, Cameras BibRef

Shi-Ning, J.[Jin], Yuan-Qing, Z.[Zhu],
Research on Pleasure Experience Design of Housekeeping APP for Middle-Aged and Elderly,
ICIVC22(963-967)
IEEE DOI 2301
Correlation, Aging, Internet, Older adults, Interviews, middle-aged and elderly users, housekeeping APP, factor analysis, experience pleasure BibRef

Tanaka, K.[Kai], Kudo, M.[Mineichi], Kimura, K.[Keigo],
Sensor Data Simulation with Wandering Behavior for the Elderly Living Alone,
ICPR22(885-891)
IEEE DOI 2212
Smart homes, Detectors, Reproducibility of results, Probability distribution, Behavioral sciences, Planning BibRef

Hao, Y.L.[Yan-Ling], Shi, Z.Y.[Zhi-Yuan], Mu, X.D.[Xi-Dong], Liu, Y.W.[Yuan-Wei],
GraSens: A Gabor Residual Anti-Aliasing Sensing Framework for Action Recognition using WiFi,
ICPR22(288-295)
IEEE DOI 2212
Sensors. Wireless communication, Wireless sensor networks, Visualization, Reliability engineering, Fractals, Sensors, Gabor filters BibRef

Chakravarthy, A.[Arnav], Fang, Z.Y.[Zhi-Yuan], Yang, Y.Z.[Ye-Zhou],
Tragedy Plus Time: Capturing Unintended Human Activities from Weakly-labeled Videos,
RoSe22(3404-3414)
IEEE DOI 2210
Location awareness, Annotations, Neural networks, Prediction algorithms, Pattern recognition, Intelligent agents BibRef

Lioupis, P.[Panagiotis], Dadoukis, A.[Aris], Maltezos, E.[Evangelos], Karagiannidis, L.[Lazaros], Amditis, A.[Angelos], Gonzalez, M.[Maite], Martin, J.[Jon], Cantero, D.[David], Larrańaga, M.[Mikel],
Embedded Intelligence for Safety and Security Machine Vision Applications,
HBAxSCES22(37-46).
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An Approach for Improving the Older people's Perception of Video-Based Applications in AAL Systems: Initial Study,
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Montoro-Lendínez, A.[Alicia], Díaz-Jiménez, D.[David], Ruiz, J.L.L.[José Luis López-], Medina-Quero, J.[Javier], Espinilla-Estévez, M.[Macarena],
Case Study of a Low-Cost IoT Device with a Thermal Vision to Monitor Human Stool Behavior in the Home,
VIAAL22(3-14).
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In-bed Posture and Night Wandering Monitoring Using Force-Sensing Resistors,
VIAAL22(28-37).
Springer DOI 2208
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Santofimia, M.J.[Maria J.], Villanueva, F.J.[Felix J.], Dorado, J.[Javier], Rubio, A.[Ana], Fernández-Bermejo, J.[Jesus], Llumiguano, H.[Henry], del Toro, X.[Xavier], Wiratunga, N.[Nirmalie], Lopez, J.C.[Juan C.],
MIRATAR: A Virtual Caregiver for Active and Healthy Ageing,
VIAAL22(49-58).
Springer DOI 2208
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Cafarelli, D.[Donato], Ciampi, L.[Luca], Vadicamo, L.[Lucia], Gennaro, C.[Claudio], Berton, A.[Andrea], Paterni, M.[Marco], Benvenuti, C.[Chiara], Passera, M.[Mirko], Falchi, F.[Fabrizio],
MOBDrone: A Drone Video Dataset for Man OverBoard Rescue,
CIAP22(II:633-644).
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Kiefer, B.[Benjamin], Ott, D.[David], Zell, A.[Andreas],
Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles,
ICPR22(3564-3571)
IEEE DOI 2212
Training, Analytical models, Object detection, Detectors, Autonomous aerial vehicles, Data models BibRef

Varga, L.A.[Leon Amadeus], Kiefer, B.[Benjamin], Messmer, M.[Martin], Zell, A.[Andreas],
SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water,
WACV22(3686-3696)
IEEE DOI 2202
Meters, Visualization, Machine vision, Training data, Object detection, Benchmark testing, Datasets, Security/Surveillance BibRef

Ileri, K., Duru, A., Karas, I.R.,
Development of IOT Enabled Global Tracking System and Mobile Application for People With Alzheimer's Disease,
SmartCityApp21(287-290).
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Laurini, E., Rotilio, M., de Berardinis, P., Tudini, B., Stornelli, V.,
Safety Monitoring By Means of Sensor Networks Distributed Within The Fossa Site Plan,
SmartCity21(55-62).
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Luo, Y.[Yiyue], Li, Y.Z.[Yun-Zhu], Foshey, M.[Michael], Shou, W.[Wan], Sharma, P.[Pratyusha], Palacios, T.[Tomás], Torralba, A.B.[Antonio B.], Matusik, W.[Wojciech],
Intelligent Carpet: Inferring 3D Human Pose from Tactile Signals,
CVPR21(11250-11260)
IEEE DOI 2111
Visualization, Solid modeling, Machine vision, Pose estimation, Smart homes, Skeleton BibRef

Yebda, T.[Thinhinane], Benois-Pineau, J.[Jenny], Pech, M.[Marion], Amieva, H.[Hélčne], Middleton, L.[Laura], Bergelt, M.[Max],
Multimodal Sensor Data Analysis for Detection of Risk Situations of Fragile People in @home Environments,
MMMod21(II:342-353).
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Codina-Filbŕ, J.[Joan], Escalera, S.[Sergio], Escudero, J.[Joan], Antens, C.[Coen], Buch-Cardona, P.[Pau], Farrús, M.[Mireia],
Mobile ehealth Platform for Home Monitoring of Bipolar Disorder,
MMMod21(II:330-341).
Springer DOI 2106
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Garcia-Ceja, E.[Enrique], Thambawita, V.[Vajira], Hicks, S.A.[Steven A.], Jha, D.[Debesh], Jakobsen, P.[Petter], Hammer, H.L.[Hugo L.], Halvorsen, P.[Pĺl], Riegler, M.A.[Michael A.],
Htad: A Home-tasks Activities Dataset with Wrist-accelerometer and Audio Features,
MMMod21(II:196-205).
Springer DOI 2106
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Pacheco, C.[Carolina], Mavroudi, E.[Effrosyni], Kokkoni, E.[Elena], Tanner, H.G.[Herbert G.], Vidal, R.[René],
A Detection-based Approach to Multiview Action Classification in Infants,
ICPR21(6112-6119)
IEEE DOI 2105
Training, Pediatrics, Fuses, Annotations, Activity recognition, Feature extraction, Cameras BibRef

Bacharidis, K.[Konstantinos], Argyros, A.[Antonis],
Extracting Action Hierarchies from Action Labels and their Use in Deep Action Recognition,
ICPR21(339-346)
IEEE DOI 2105
Vocabulary, Surveillance, Semantics, Smart homes, Organizations, Linguistics, Activity recognition BibRef

Simonsson, S.[Simon], Casagrande, F.D.[Flávia Dias], Zouganeli, E.[Evi],
Location Prediction in Real Homes of Older Adults based on K-Means in Low-Resolution Depth Videos,
ICPR21(9046-9053)
IEEE DOI 2105
Training, Image sensors, Neural networks, Memory management, Clustering algorithms, Smart homes, Semisupervised learning BibRef

Cerit, B., Bayir, R.,
Deep Learning Based Mask Detection In Smart Home Entries During The Epidemic Process,
SmartCityApp20(159-163).
DOI Link 2012
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Pramerdorfer, C., Planinc, R., Kampel, M.,
Effective Deep-Learning-Based Depth Data Analysis on Low-Power Hardware for Supporting Elderly Care,
LPCV20(1584-1590)
IEEE DOI 2008
Hardware, Senior citizens, Neural networks, Motion detection, Tracking, Monitoring BibRef

Gladisch, C., Heinzemann, C., Herrmann, M., Woehrle, M.,
Leveraging combinatorial testing for safety-critical computer vision datasets,
SAIAD20(1314-1321)
IEEE DOI 2008
Testing, Tools, Computational modeling, Analytical models, Context modeling, Software BibRef

Hanosh, O., Ansari, R., Issa, N.P., Cetin, A.E.[A. Enis],
Convulsive Movement Detection using Low-Resolution Thermopile Sensor Array,
CVPM20(1217-1223)
IEEE DOI 2008
Sensor arrays, Feature extraction, Machine learning, Sleep, Thermal sensors, Measurement BibRef

Sebastiani, M., Garau, N., de Natale, F., Conci, N.,
Joint Trajectory and Fatigue Analysis in Wheelchair Users,
ACVR19(2629-2637)
IEEE DOI 2004
Trajectory, Wheelchairs, Cameras, Fatigue, Shoulder, Skeleton, Electromyography, trajectory, fatigue, analysis, pose estimation, motor skills BibRef

Grimaldo, A.I.[Ana I.], Novak, J.[Jasminko],
User-Centered Visual Analytics Approach for Interactive and Explainable Energy Demand Analysis in Prosumer Scenarios,
CVS19(700-710).
Springer DOI 1912
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Chouliara, A.[Adamantia], Peppas, K.[Konstantinos], Tsolakis, A.C.[Apostolos C.], Vafeiadis, T.[Thanasis], Krinidis, S.[Stelios], Tzovaras, D.[Dimitrios],
Occupancy Inference Through Energy Consumption Data: A Smart Home Experiment,
CVS19(670-679).
Springer DOI 1912
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Sobue, R., Nakazawa, M., Chae, Y., Stenger, B., Yamashita, T., Fujiyoshi, H.,
Cooking Video Summarization Guided By Matching with Step-By-Step Recipe Photos,
MVA19(1-6)
DOI Link 1911
feature extraction, human computer interaction, humanities, social networking (online), video signal processing, Resource management BibRef

Ishikawa, H., Ishikawa, Y., Akizuki, S., Aoki, Y.,
Human-Object Maps for Daily Activity Recognition,
MVA19(1-6)
DOI Link 1911
image recognition, image representation, time frame, spatio-temporal information, Signal to noise ratio BibRef

Wang, T.J., Laaksonen, J.T., Liao, Y., Wu, B., Shen, S.,
A Multi-Task Bayesian Deep Neural Net for Detecting Life-Threatening Infant Incidents From Head Images,
ICIP19(3006-3010)
IEEE DOI 1910
Bayesian deep neural net, occlusion detection, cover detection, neonate safety BibRef

He, S.[Shuang], Jia, Y.H.[Yan-Hong], Sun, Z.[Zhe], Yu, C.X.[Chen-Xin], Yi, X.[Xin], Shi, Y.C.[Yuan-Chun], Xu, Y.Q.[Ying-Qing],
AR Assistive System in Domestic Environment Using HMDs: Comparing Visual and Aural Instructions,
VAMR19(I:71-83).
Springer DOI 1909
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Puig, X., Ra, K., Boben, M., Li, J., Wang, T., Fidler, S.[Sanja], Torralba, A.B.[Antonio B.],
VirtualHome: Simulating Household Activities Via Programs,
CVPR18(8494-8502)
IEEE DOI 1812
Task analysis, Robots, Videos, Natural languages, Games, TV, Engines BibRef

Choe, J., Montserrat, D.M., Schwichtenberg, A.J., Delp, E.J.,
Sleep Analysis Using Motion and Head Detection,
Southwest18(29-32)
IEEE DOI 1809
Head, Indexes, Sleep, Feature extraction, Encoding, Motion segmentation, Cameras, videosomnography, motion detection, head detection BibRef

Baba, E., Jilbab, A., Hammouch, A.,
A health remote monitoring application based on wireless body area networks,
ISCV18(1-4)
IEEE DOI 1807
body area networks, body sensor networks, graphical user interfaces, health care, remote patient health monitoring BibRef

Ngabo, C.I., El Beqqali, O.,
3D tilt sensing by using accelerometer-based wireless sensor networks: Real case study: Application in the smart cities,
ISCV18(1-8)
IEEE DOI 1807
accelerometers, angular measurement, poles and towers, power system measurement, sensors, smart cities, Wireless Sensor Networks BibRef

Sun, Y.J.[Yi-Jie], Zhang, Y.[Yuan], Zhao, R.[Rong], Chen, Y.Q.[Yan-Qiu],
Safety Performance Evaluation for Civil Aviation Maintenance Department,
DHM18(635-646).
Springer DOI 1807
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Ogata, K.[Kunihiro], Matsumoto, Y.[Yoshio], Kajitani, I.[Isamu], Homma, K.[Keiko], Wakita, Y.J.[Yu-Jin],
Whole-Body Robotic Simulator of the Elderly for Evaluating Robotic Devices for Nursing Care,
DHM18(478-487).
Springer DOI 1807
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Ortiz-Barrios, M.[Miguel], Neira-Rodado, D.[Dionicio], Jiménez-Delgado, G.[Genett], McClean, S.[Sally], Lara, O.[Osvaldo],
Definition of Strategies for the Reduction of Operational Inefficiencies in a Stroke Unit,
DHM18(488-501).
Springer DOI 1807
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Wang, F.H.[Feng-Hong], Zeng, Z.W.[Zhen-Wen], Lin, L.[Lin],
Research on Motor Function of the Elderly in Guangzhou Based on Anthropometry,
DHM18(232-241).
Springer DOI 1807
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Nakagawa, H.[Hiromi], Tukamoto, M.[Masahiro], Yamashiro, K.[Kazuaki], Goto, A.[Akihiko],
Motion Analysis of Simulated Patients During Bed-to-Wheelchair Transfer by Nursing Students and Skill Acquisition Based on the Analysis,
DHM18(193-204).
Springer DOI 1807
BibRef

Konno, K.[Kanako], Kuwahara, N.[Noriaki],
Study of Improving a Welfare Workplace by Surveying Good Standing Companies of Employment of People with Disabilities,
DHM18(75-84).
Springer DOI 1807
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Nickel, P.[Peter], Lungfiel, A.[Andy],
Improving Occupational Safety and Health (OSH) in Human-System Interaction (HSI) Through Applications in Virtual Environments,
DHM18(85-96).
Springer DOI 1807
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Li, B., Bouachir, W., Gouiaa, R., Noumeir, R.,
Real-time recognition of suicidal behavior using an RGB-D camera,
IPTA17(1-6)
IEEE DOI 1804
feature extraction, image colour analysis, image motion analysis, image recognition, object detection, video surveillance BibRef

Lilja, K.K., Palomäki, J.,
The use of advanced imaging technology in welfare technology solutions: Some ethical aspects,
3DTV-CON17(1-4)
IEEE DOI 1804
ethical aspects, image processing, advanced imaging technology, ethical aspects, welfare technology solutions, Cameras, Ethics, welfare technology BibRef

Abebe, G., Cavallaro, A.,
Inertial-Vision: Cross-Domain Knowledge Transfer for Wearable Sensors,
ACVR17(1392-1400)
IEEE DOI 1802
Feature extraction, Logistics, Spectrogram, Videos, Visualization BibRef

Perrett, T.[Toby], Damen, D.[Dima],
DDLSTM: Dual-Domain LSTM for Cross-Dataset Action Recognition,
CVPR19(7844-7853).
IEEE DOI 2002
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Earlier:
Recurrent Assistance: Cross-Dataset Training of LSTMs on Kitchen Tasks,
ACVR17(1354-1362)
IEEE DOI 1802
Feature extraction, Real-time systems, Support vector machines, Training, Videos BibRef

Liu, S., Ostadabbas, S.,
A Vision-Based System for In-Bed Posture Tracking,
ACVR17(1373-1382)
IEEE DOI 1802
Cameras, Feature extraction, Histograms, Hospitals, Monitoring, Videos BibRef

Wu, T.Y.[Tz-Ying], Chien, T.A.[Ting-An], Chan, C.S.[Cheng-Sheng], Hu, C.W.[Chan-Wei], Sun, M.[Min],
Anticipating Daily Intention Using On-wrist Motion Triggered Sensing,
ICCV17(48-56)
IEEE DOI 1802
entropy, expert systems, recurrent neural nets, Policy Network, RNN, cross-entropy loss, intelligent system, motion observation, Visualization BibRef

Vlasselaer, J., Crispim-Junior, C.F., Bremond, F., Dries, A.,
BEHAVE: Behavioral Analysis of Visual Events for Assisted Living Scenarios,
ACVR17(1347-1353)
IEEE DOI 1802
Assisted living, Mathematical model, Pipelines, Probabilistic logic, Sensors, Visualization BibRef

Mocanu, I.[Irina], Cramariuc, B.[Bogdan], Balan, O.[Oana], Moldoveanu, A.[Alin],
A Framework for Activity Recognition Through Deep Learning and Abnormality Detection in Daily Activities,
CIAP17(II:730-740).
Springer DOI 1711
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Agrigoroaie, R.[Roxana], Tapus, A.[Adriana],
Contactless Physiological Data Analysis for User Quality of Life Improving by Using a Humanoid Social Robot,
CIAP17(II:696-706).
Springer DOI 1711
BibRef

Zeng, K.H., Chou, S.H., Chan, F.H., Niebles, J.C.[Juan Carlos], Sun, M.,
Agent-Centric Risk Assessment: Accident Anticipation and Risky Region Localization,
CVPR17(1330-1338)
IEEE DOI 1711
Accidents, Recurrent neural networks, Risk management, Trajectory, Videos, Visualization BibRef

Wang, H., van Zon, K., Kirenko, I., Rocque, M.,
Monitoring Patients in the Wild,
FG17(997-997)
IEEE DOI 1707
Biomedical monitoring, Cameras, Face, Monitoring, Prototypes, Pulse, measurements BibRef

Chen, W., Picard, R.W.,
Eliminating Physiological Information from Facial Videos,
FG17(48-55)
IEEE DOI 1707
Biomedical monitoring, Cameras, Image color analysis, Laplace equations, Physiology, Principal component analysis, Videos BibRef

Vaquette, G., Orcesi, A., Lucat, L., Achard, C.,
The DAily Home LIfe Activity Dataset: A High Semantic Activity Dataset for Online Recognition,
FG17(497-504)
IEEE DOI 1707
Dataset, Smart Home. Cameras, Databases, Protocols, Semantics, Sensors, Skeleton, Videos BibRef

Zaouali, K., Ammari, M.L., Bouallegue, R., Sahloul, I., Chouaieb, A.,
Incoming data prediction in smart home environment with HMM-based machine learning,
ISIVC16(384-389)
IEEE DOI 1704
Data mining;Hidden-Markov model;Smart home;Wireless sensor network BibRef

Tao, L.[Lili], Burghardt, T.[Tilo], Mirmehdi, M.[Majid], Damen, D.[Dima], Cooper, A.[Ashley], Hannuna, S.[Sion], Camplani, M.[Massimo], Paiement, A.[Adeline], Craddock, I.[Ian],
Calorie Counter: RGB-Depth Visual Estimation of Energy Expenditure at Home,
Assist16(I: 239-251).
Springer DOI 1704
BibRef

Meditskos, G.[Georgios], Vrochidis, S.[Stefanos], Kompatsiaris, I.[Ioannis],
Description Logics and Rules for Multimodal Situational Awareness in Healthcare,
MMMod17(I: 714-725).
Springer DOI 1701
BibRef

Bonderup, S.[Soren], Olsson, J.[Jonas], Bonderup, M.[Morten], Moeslund, T.B.[Thomas B.],
Preventing Drowning Accidents Using Thermal Cameras,
ISVC16(II: 111-122).
Springer DOI 1701
BibRef

Gupta, O., McDuff, D., Raskar, R.,
Real-Time Physiological Measurement and Visualization Using a Synchronized Multi-camera System,
PBVS16(312-319)
IEEE DOI 1612
BibRef

Ohnishi, K., Kanehira, A., Kanezaki, A., Harada, T.,
Recognizing Activities of Daily Living with a Wrist-Mounted Camera,
CVPR16(3103-3111)
IEEE DOI 1612
BibRef

Aran, O.[Oya], Sanchez-Cortes, D.[Dairazalia], Do, M.T.[Minh-Tri], Gatica-Perez, D.[Daniel],
Anomaly Detection in Elderly Daily Behavior in Ambient Sensing Environments,
HBU16(51-67).
Springer DOI 1611
BibRef

Vincze, M.[Markus], Bajones, M.[Markus], Suchi, M.[Markus], Wolf, D.[Daniel], Weiss, A.[Astrid], Fischinger, D.[David], da la Puente, P.[Paloma],
Learning and Detecting Objects with a Mobile Robot to Assist Older Adults in Their Homes,
ACVR16(II: 316-330).
Springer DOI 1611
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Torres, C.[Carlos], Fried, J.C.[Jeffrey C.], Rose, K.[Kenneth], Manjunath, B.S.,
Deep Eye-CU (DECU): Summarization of Patient Motion in the ICU,
ACVR16(II: 178-194).
Springer DOI 1611
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Sigurdsson, G.A.[Gunnar A.], Varol, G.[Gül], Wang, X.L.[Xiao-Long], Farhadi, A.[Ali], Laptev, I.[Ivan], Gupta, A.[Abhinav],
Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding,
ECCV16(I: 510-526).
Springer DOI 1611
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Chen, C.R., Chen, C.F., Liu, M.E., Tsai, S.J., Son, N.T., Kinh, L.V.,
Mining Spatiotemporal Patterns Of The Elder's Daily Movement,
ISPRS16(B2: 505-507).
DOI Link 1610
Wearable sensor. BibRef

Tezcan, M.O., Konrad, J., Muroff, J.,
Automatic Assessment of Hoarding Clutter from Images Using Convolutional Neural Networks,
Southwest18(1-4)
IEEE DOI 1809
Clutter, Support vector machines, Training, Measurement, Convolutional neural networks, Visualization, convolutional neural networks BibRef

Tooke, A., Konrad, J., Muroff, J.,
Towards automatic assessment of compulsive hoarding from images,
ICIP16(1324-1328)
IEEE DOI 1610
Clothing BibRef

Ott, T.[Tammy], Wu, P.[Peggy], Morie, J.[Jacki], Wall, P.[Peter], Ladwig, J.[Jack], Chance, E.[Eric], Haynes, K.[Kip], Bell, B.[Bryan], Miller, C.[Christopher], Binsted, K.[Kim],
ANSIBLE: A Virtual World Ecosystem for Improving Psycho-Social Well-being,
VAMR16(532-543).
Springer DOI 1608
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Vu, H.[Huyen], Eftestřl, T.[Trygve], Engan, K.[Kjersti], Eilevstjřnn, J.[Joar], Yarrot, L.B.[Ladislaus Blacy], Linde, J.E.[Jřrgen E.], Ersdal, H.[Hege],
Detection of Activities During Newborn Resuscitation Based on Short-Time Energy of Acceleration Signal,
ICISP16(262-270).
WWW Link. 1606
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Torres, C.[Carlos], Fragoso, V., Hammond, S.D., Fried, J.C.[Jeffrey C.], Manjunath, B.S.,
Eye-CU: Sleep pose classification for healthcare using multimodal multiview data,
WACV16(1-9)
IEEE DOI 1511
Cameras BibRef

Siebra, C.A., Sá, B.A., Gouveia, T.B., Silva, F.Q.B., Santos, A.L.M.,
A neural network based application for remote monitoring of human behaviour,
ICCVIA15(1-6)
IEEE DOI 1603
accelerometers BibRef

Fang, C.Y., Hsieh, H.H., Chen, S.W.,
A Vision-Based Infant Respiratory Frequency Detection System,
DICTA15(1-8)
IEEE DOI 1603
computer vision BibRef

Palenichka, R., Lakhssassi, A., Palenichka, M.,
Visual Attention-Guided Approach to Monitoring of Medication Dispensing Using Multi-location Feature Saliency Patterns,
ACVR15(461-468)
IEEE DOI 1602
Biomedical imaging BibRef

Okamoto, K.[Koichi], Yanai, K.[Keiji],
GrillCam: A Real-Time Eating Action Recognition System,
MMMod16(II: 331-335).
Springer DOI 1601
BibRef

Mecocci, A.[Alessandro], Micheli, F.[Francesco], Zoppetti, C.[Claudia],
Range Image Processing for Real Time Hospital-Room Monitoring,
ISVC15(II: 81-92).
Springer DOI 1601
BibRef

Schwarze, T.[Tobias], Zhong, Z.C.[Zhi-Chao],
Stair detection and tracking from egocentric stereo vision,
ICIP15(2690-2694)
IEEE DOI 1512
Environment perception; Object tracking; Scene Reconstruction BibRef

Hoang, T.N., Foloppe, D.A., Richard, P.,
Tangible virtual kitchen for the rehabilitation of Alzheimer's patients,
3DUI15(161-162)
IEEE DOI 1511
human computer interaction BibRef

Bergenti, F.[Federico], Chiappone, M.[Massimo], Gotta, D.[Danilo],
Smart Maintenance to Support Digital Life,
ISCA15(226-233).
Springer DOI 1511
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Mohadis, H.M.[Hazwani Mohd], Ali, N.M.[Nazlena Mohamad], Shahar, S.[Suzana], Smeaton, A.F.[Alan F.],
Web-Based Physical Activity Interventions for Older Adults: A Review,
IVIC15(405-419).
Springer DOI 1511
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Sin, A.K.[Aw Kien], Zaman, H.B.[Halimah Badioze], Ahmad, A.[Azlina], Sulaiman, R.[Riza],
Evaluation of Wearable Device for the Elderly (W-Emas),
IVIC15(119-131).
Springer DOI 1511
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Ranjan, J.[Juhi], Whitehouse, K.[Kamin],
Rethinking the Fusion of Technology and Clinical Practices in Functional Behavior Analysis for the Elderly,
HBUI15(52-65).
Springer DOI 1511
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Kanis, M.[Marije], Robben, S.[Saskia], Kröse, B.J.A.[Ben J.A.],
How Are You Doing? Enabling Older Adults to Enrich Sensor Data with Subjective Input,
HBUI15(39-51).
Springer DOI 1511
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Eldib, M.[Mohamed], Deboeverie, F.[Francis], Philips, W.[Wilfried], Aghajan, H.[Hamid],
Sleep Analysis for Elderly Care Using a Low-Resolution Visual Sensor Network,
HBUI15(26-38).
Springer DOI 1511
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Jaschinski, C.[Christina], Ben Allouch, S.[Somaya],
Understanding the User's Acceptance of a Sensor-Based Ambient Assisted Living Application,
HBUI15(13-25).
Springer DOI 1511
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Salah, A.A.[Albert Ali], Kröse, B.J.A.[Ben J.A.], Cook, D.J.[Diane J.],
Behavior Analysis for Elderly,
HBUI15(1-10).
Springer DOI 1511
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Hernández, N.[Netzahualcóyotl], Favela, J.[Jesús],
Estimating the Perception of Physical Fatigue Among Older Adults Using Mobile Phones,
HBUI15(84-96).
Springer DOI 1511
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Grisales-Franco, F.M.[Fily M.], Vargas, F.[Francisco], Orozco, Á.Á.[Álvaro Ángel], Alvarezz, M.A.[Mauricio A.], Soto-Mendoza, V.[Valeria], Beltrán, J.[Jessica], Chávez, E.[Edgar], Hernández, J.[Jehú], García-Macías, J.A.[J. Antonio],
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HBUI15(119-131).
Springer DOI 1511
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Lago, P.[Paula], Jiménez-Guarín, C.[Claudia], Roncancio, C.[Claudia],
Contextualized Behavior Patterns for Ambient Assisted Living,
HBUI15(132-145).
Springer DOI 1511
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Derungs, A.[Adrian], Seiter, J.[Julia], Schuster-Amft, C.[Corina], Amft, O.[Oliver],
Activity Patterns in Stroke Patients: Is There a Trend in Behaviour During Rehabilitation?,
HBUI15(146-159).
Springer DOI 1511
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Moshnyaga, V.[Vasily], Osamu, T.[Tanaka], Ryu, T.[Toshin], Hashimoto, K.[Koji],
Identification of Basic Behavioral Activities by Heterogeneous Sensors of In-Home Monitoring System,
HBUI15(160-174).
Springer DOI 1511
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Torres, C.[Carlos], Hammond, S.D.[Scott D.], Fried, J.C.[Jeffrey C.], Manjunath, B.S.,
Sleep Pose Recognition in an ICU Using Multimodal Data and Environmental Feedback,
CVS15(56-66).
Springer DOI 1507
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Martinez, M.[Manuel], Rybok, L.[Lukas], Stiefelhagen, R.[Rainer],
Action recognition in bed using BAMs for assisted living and elderly care,
MVA15(329-332)
IEEE DOI 1507
Accidents BibRef

Tayyub, J.[Jawad], Tavanai, A.[Aryana], Gatsoulis, Y.F.[Yi-Fannis], Cohn, A.G.[Anthony G.], Hogg, D.C.[David C.],
Qualitative and Quantitative Spatio-temporal Relations in Daily Living Activity Recognition,
ACCV14(V: 115-130).
Springer DOI 1504
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Iscen, A.[Ahmet], Wang, Y.J.[Yi-Jie], Duygulu, P.[Pinar], Hauptmann, A.G.[Alex G.],
Snippet Based Trajectory Statistics Histograms for Assistive Technologies,
ACVR14(3-16).
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For home use of medical devices. BibRef

Perez-Yus, A.[Alejandro], Lopez-Nicolas, G.[Gonzalo], Guerrero, J.J.[Jose J.],
Peripheral Expansion of Depth Information via Layout Estimation with Fisheye Camera,
ECCV16(VIII: 396-412).
Springer DOI 1611
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Pérez-Yus, A.[Alejandro], López-Nicolás, G.[Gonzalo], Guerrero, J.J.[José J.],
Detection and Modelling of Staircases Using a Wearable Depth Sensor,
ACVR14(449-463).
Springer DOI 1504
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Konda, K.R.[Krishna Reddy], Rosani, A.[Andrea], Conci, N.[Nicola], de Natale, F.G.B.[Francesco G. B.],
Smart Camera Reconfiguration in Assisted Home Environments for Elderly Care,
ACVR14(45-58).
Springer DOI 1504
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Giakoumis, D.[Dimitris], Stavropoulos, G.[Georgios], Kikidis, D.[Dimitrios], Vasileiadis, M.[Manolis], Votis, K.[Konstantinos], Tzovaras, D.[Dimitrios],
Recognizing Daily Activities in Realistic Environments Through Depth-Based User Tracking and Hidden Conditional Random Fields for MCI/AD Support,
ACVR14(822-838).
Springer DOI 1504
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Fahad, L.G.[Labiba Gillani], Tahir, S.F.[Syed Fahad], Rajarajan, M.[Muttukrishnan],
Activity Recognition in Smart Homes Using Clustering Based Classification,
ICPR14(1348-1353)
IEEE DOI 1412
Accuracy BibRef

Jalal, A.[Ahmad], Kamal, S.,
Real-time life logging via a depth silhouette-based human activity recognition system for smart home services,
AVSS14(74-80)
IEEE DOI 1411
Cameras BibRef

Saracchini, R.F.V.[Rafael F. V.], Ortega, C.C.[Carlos C.],
An Easy to Use Mobile Augmented Reality Platform for Assisted Living Using Pico-projectors,
ICCVG14(552-561).
Springer DOI 1410
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Sha, L.[Long], Lucey, P.[Patrick], Sridharan, S.[Sridha], Morgan, S.[Stuart], Pease, D.[Dave],
Understanding and analyzing a large collection of archived swimming videos,
WACV14(674-681)
IEEE DOI 1406
Calibration BibRef

Sha, L.[Long], Lucey, P., Morgan, S., Pease, D., Sridharan, S.,
Swimmer Localization from a Moving Camera,
DICTA13(1-8)
IEEE DOI 1402
computer vision BibRef

Malmir, M., Forster, D., Youngstrom, K., Morrison, L., Movellan, J.R.,
Home Alone: Social Robots for Digital Ethnography of Toddler Behavior,
SocialInter13(762-768)
IEEE DOI 1403
behavioural sciences computing BibRef

Bansal, S.[Shubham], Khandelwal, S.[Shubham], Gupta, S.[Shubham], Goyal, D.[Dushyant],
Kitchen activity recognition based on scene context,
ICIP13(3461-3465)
IEEE DOI 1402
Cooking Activity Recognition; Frame Classification; Kinect; Kitchen BibRef

Zoidi, O.[Olga], Tefas, A.[Anastasios], Pitas, I.[Ioannis],
Exploiting the SVM constraints in NMF with application in eating and drinking activity recognition,
ICIP13(3765-3769)
IEEE DOI 1402
Joint Optimization BibRef

Crispim-Junior, C.F.[Carlos Fernando], Bathrinarayanan, V.[Vasanth], Fosty, B.[Baptiste], Konig, A.[Alexandra], Romdhane, R.[Rim], Thonnat, M.[Monique], Bremond, F.[Francois],
Evaluation of a monitoring system for event recognition of older people,
AVSS13(165-170)
IEEE DOI 1311
Accuracy; Alzheimer's disease; Cameras; Monitoring; Prototypes; Sensors BibRef

Rostamzadeh, N.[Negar], Zen, G.[Gloria], Mironica, I.[Ionut], Uijlings, J.[Jasper], Sebe, N.[Nicu],
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CIAP13(I:431-441).
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Wang, R.Z.[Rui-Zhe], Medioni, G.[Gerard], Winstein, C.J.[Carolee J.], Blanco, C.[Cesar],
Home Monitoring Musculo-skeletal Disorders with a Single 3D Sensor,
HAU3D13(521-528)
IEEE DOI 1309
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Chakraborty, I., Elgammal, A.M., Burd, R.S.[Randall S.],
Video based activity recognition in trauma resuscitation,
FG13(1-8)
IEEE DOI 1309
Markov processes BibRef

Martinez, M.[Manuel], Schauerte, B.[Boris],
'BAM!' Depth-Based Body Analysis in Critical Care,
CAIP13(465-472).
Springer DOI 1308
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Lee, S.[Sukhan], Ilyas, M., Jaewoong, K.[Kim], Naguib, A.,
Evidence filtering in a sequence of images for recognition,
AIPR12(1-8)
IEEE DOI 1307
belief networks. Image sequences using Particle filter in HomeMate Robot application. BibRef

Somei, T.[Takayuki], Kobayashi, Y.[Yuichi], Shimizu, A.[Akinobu], Kaneko, T.[Toru],
Clustering of image features based on contact and occlusion among robot body and objects,
WORV13(203-208)
IEEE DOI 1307
Keypoints clustered by motions and occlusions. Separate robot body from objects. BibRef

Ohshima, Y., Kobayashi, Y., Kaneko, T., Yamashita, A., Asama, H.,
Meal support system with spoon using laser range finder and manipulator,
WORV13(82-87)
IEEE DOI 1307
dexterous manipulators BibRef

Lin, Q.A.[Qi-Ang], Zhang, D.Q.[Da-Qing], Huang, X.D.[Xiao-Di], Ni, H.B.[Hong-Bo], Zhou, X.S.[Xing-She],
Detecting wandering behavior based on GPS traces for elders with dementia,
ICARCV12(672-677).
IEEE DOI 1304
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Hussain, M., Afzal, M., Khan, W.A., Lee, S.Y.[Sung-Young],
Clinical Decision Support Service for elderly people in smart home environment,
ICARCV12(678-683).
IEEE DOI 1304
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Yamazaki, T.[Tatsuya],
Communicative robot interface for the ageing society,
ICARCV12(668-671).
IEEE DOI 1304
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Kobayashi, H., Hino, Y., Ho, I., Pham, B., Watanabe, S.,
Information and communication technology-based tele-monitoring for elderly care houses,
ICARCV12(662-667).
IEEE DOI 1304
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Zhang, M.[Mi], Xu, W.[Wenyao], Sawchuk, A.A.[Alexander A.], Sarrafzadeh, M.[Majid],
Sparse representation for motion primitive-based human activity modeling and recognition using wearable sensors,
ICPR12(1807-1810).
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Wang, Y.[Yu], Kato, J.[Jien],
A distance metric learning based summarization system for nursery school surveillance video,
ICIP12(37-40).
IEEE DOI 1302
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Parra-Dominguez, G.S.[Gemma S.], Taati, B.[Babak], Mihailidis, A.[Alex],
3D Human Motion Analysis to Detect Abnormal Events on Stairs,
3DIMPVT12(97-103).
IEEE DOI 1212
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Zhou, Q.A.[Qi-Ang], Wang, G.[Gang],
Learning to Recognize Unsuccessful Activities Using a Two-Layer Latent Structural Model,
ECCV12(III: 750-763).
Springer DOI 1210
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Wiesmann, G.[Georg], Schraml, S.[Stephan], Litzenberger, M.[Martin], Belbachir, A.N.[Ahmed Nabil], Hofstatter, M.[Michael], Bartolozzi, C.[Chiara],
Event-driven embodied system for feature extraction and object recognition in robotic applications,
ECVW12(76-82).
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AVSS13(371-376)
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Acceleration BibRef

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AVSS10(278-285).
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Earlier:
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IEEE DOI 0909
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Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Human Safety, Falling, Fall Detection, Home Care, Smart Home .


Last update:Mar 16, 2024 at 20:36:19