16.7.4.7.5 Human Safety, Falling, Drowning, Underwater, Home Care, Smart Home

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

Lu, W.[Wenmiao], 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

Brodsky, T.[Tomas], Dagtas, S.[Serhan],
Video based detection of fall-down and other events,
US_Patent7,110,569, Sep 19, 2006
WWW Link. BibRef 0609

McKenna, S.J.[Stephen J.], Nait-Charif, H.[Hammadi],
Summarising Contextual Activity and Detecting Unusual Inactivity in a Supportive Home Environment,
PAA(7), No. 4, December 2004, pp. 386-401.
PDF File. BibRef 0412
Earlier: A2, A1:
Activity summarisation and fall detection in a supportive home environment,
ICPR04(IV: 323-326).
IEEE DOI 0409
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.
WWW Link. 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

Anderson, D.T.[Derek T.], Luke, R.H.[Robert H.], Keller, J.M.[James M.], Skubic, M.[Marjorie], Rantz, M.[Marilyn], Aud, M.[Myra],
Linguistic summarization of video for fall detection using voxel person and fuzzy logic,
CVIU(113), No. 1, January 2009, pp. 80-89.
Elsevier DOI 0812
Linguistic summarization; Activity analysis; Fuzzy logic; Fall detection; Eldercare; Voxel person 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.
WWW Link. 0711
Behavior recognition; Duration HMM; Hierarchical HMM; Context BibRef

Thome, N.[Nicolas], Miguet, S.[Serge], Ambellouis, S.,
A Real-Time, Multiview Fall Detection System: A LHMM-Based Approach,
CirSysVideo(18), No. 11, November 2008, pp. 1522-1532.
IEEE DOI 0811
BibRef
Earlier: A1, A2, Only:
A HHMM-Based Approach for Robust Fall Detection,
ICARCV06(1-8).
IEEE DOI 0612
BibRef
Earlier: A1, A2, Only:
A robust appearance model for tracking human motions,
AVSBS05(528-533).
IEEE DOI 0602
BibRef

Thome, N.[Nicolas], Merad, D.[Djamel], Miguet, S.[Serge],
Learning articulated appearance models for tracking humans: A spectral graph matching approach,
SP:IC(23), No. 10, November 2008, pp. 769-787,.
Elsevier DOI 0804
BibRef
Earlier:
Human Body Part Labeling and Tracking Using Graph Matching Theory,
AVSBS06(38-38).
IEEE DOI 0611
Real-time multiple people tracking; On-line articulated appearance learning; People identification; Body part labeling from silhouette; Spectral graph matching; Topological model BibRef

Pop, I.[Ionel], Mihaela, S.[Scuturici], Miguet, S.[Serge],
Common Motion Map Based on Codebooks,
ISVC09(II: 1181-1190).
Springer DOI 0911
BibRef

Pop, I.[Ionel], Mihaela, S.[Scuturici], Miguet, S.[Serge],
Incremental trajectory aggregation in video sequences,
ICPR08(1-4).
IEEE DOI 0812
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.
WWW Link. 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

Lai, C.F.[Chin-Feng], Huang, Y.M.[Yueh-Min], Park, J.H.[Jong Hyuk], Chao, H.C.[Han-Chieh],
Adaptive Body Posture Analysis for Elderly-Falling Detection with Multisensors,
IEEE_Int_Sys(25), No. 2, March-April 2010, pp. 20-30.
IEEE DOI 1006
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.
WWW Link. 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

Rougier, C., Meunier, J.[Jean], St-Arnaud, A.[Alain], Rousseau, J.[Jacqueline],
Robust Video Surveillance for Fall Detection Based on Human Shape Deformation,
CirSysVideo(21), No. 5, May 2011, pp. 611-622.
IEEE DOI 1105
BibRef

Auvinet, E.[Edouard], Multon, F.[Franck], St-Arnaud, A.[Alain], Rousseau, J.[Jacqueline], Meunier, J.[Jean],
Fall Detection Using Body Volume Recontruction and Vertical Repartition Analysis,
ICISP10(376-383).
Springer DOI 1006
BibRef

Liao, Y.T.[Yi Ting], Huang, C.L.[Chung-Lin], Hsu, S.C.[Shih-Chung],
Slip and fall event detection using Bayesian Belief Network,
PR(45), No. 1, January 2012, pp. 24-32.
Elsevier DOI 1109
BibRef
Earlier: A1, A2, Only:
Slip and Fall Events Detection by Analyzing the Integrated Spatiotemporal Energy Map,
ICPR10(1718-1721).
IEEE DOI 1008
Bayesian Belief Network (BBN); Slip and fall event detection; Motion history image (MHI); Integrated spatiotemporal energy (ISTE) map; Motion active (MA) area 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

Yu, M., Naqvi, S.M., Rhuma, A., Chambers, J.,
One class boundary method classifiers for application in a video-based fall detection system,
IET-CV(6), No. 2, 2012, pp. 90-100.
DOI Link 1204
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,
Artificial Intelligence(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

Rougier, C.[Caroline], Meunier, J.[Jean], St-Arnaud, A.[Alain], Rousseau, J.[Jacqueline],
3D head tracking for fall detection using a single calibrated camera,
IVC(31), No. 3, March 2013, pp. 246-254.
Elsevier DOI 1303
Computer vision; 3D; Head tracking; Monocular; Particle Filter; Video surveillance; Fall detection 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

Yazar, A.[Ahmet], Keskin, F.[Furkan], Töreyin, B.U.[B. Ugur], Çetin, A.E.[A. Enis],
Fall detection using single-tree complex wavelet transform,
PRL(34), No. 15, 2013, pp. 1945-1952.
Elsevier DOI 1309
Vibration sensor BibRef

Katz, P.[Philippe], Aron, M.[Michael], Alfalou, A.[Ayman],
A face-tracking system to detect falls in the elderly,
SPIE(Newsroom), August 8, 2013.
DOI Link 1310
An automated surveillance method that uses multiple image processing can detect, analyze, and track movements to identify emergency situations. 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

Zhang, X.[Xinpeng], 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.[Bas], 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.
WWW Link. 1407
Ph.D.. Thesis. BibRef

Grewe, L.[Lynne], Magańa-Zook, S.[Steven],
Building a cyber-physical fall detection system for seniors,
SPIE(Newsroom), April 17, 2014
DOI Link 1407
A 3D commercial vision sensor helps older people live autonomously at home for longer. BibRef

Suryadevara, N.K.[Nagender K.], Mukhopadhyay, S.C.[Subhas C.],
Determining Wellness through an Ambient Assisted Living Environment,
IEEE_Int_Sys(29), No. 3, May 2014, pp. 30-37.
IEEE DOI 1408
Aging BibRef

Feng, W.G.[Wei-Guo], Liu, R.[Rui], Zhu, M.[Ming],
Fall detection for elderly person care in a vision-based home surveillance environment using a monocular camera,
SIViP(8), No. 6, September 2014, pp. 1129-1138.
Springer DOI 1408
BibRef

Mastorakis, G.[Georgios], Makris, D.[Dimitrios],
Fall detection system using Kinect's infrared sensor,
RealTimeIP(9), No. 4, December 2014, pp. 635-646.
WWW Link. 1411
BibRef

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

Kirkpatrick, K.[Keith],
Sensors for Seniors,
CACM(57), No. 12, December 2014, pp. 17-19.
DOI Link 1412
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

Chua, J.L.[Jia-Luen], Chang, Y.C.[Yoong Choon], Lim, W.K.[Wee Keong],
A simple vision-based fall detection technique for indoor video surveillance,
SIViP(9), No. 3, March 2015, pp. 623-633.
WWW Link. 1503
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

Fortin-Simard, D.[Dany], Bilodeau, J.S.[Jean-Sebastien], Bouchard, K.[Kevin], Gaboury, S.[Sebastien], Bouchard, B.[Bruno], Bouzouane, A.[Abdenour],
Exploiting Passive RFID Technology for Activity Recognition in Smart Homes,
IEEE_Int_Sys(30), No. 4, July 2015, pp. 7-15.
IEEE DOI 1506
Ambient networks BibRef

Parada, R.[Raul], Melia-Segui, J.[Joan], Morenza-Cinos, M.[Marc], Carreras, A.[Anna], Pous, R.[Rafael],
Using RFID to Detect Interactions in Ambient Assisted Living Environments,
IEEE_Int_Sys(30), No. 4, July 2015, pp. 16-22.
IEEE DOI 1506
Ambient networks BibRef

Lee, Y.[Yuju], 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

Waterson, P.E., Kendrick, V.L., Ryan, B., Jun, T., Haslam, R.A.,
Probing deeper into the risks of slips, trips and falls for an ageing rail passenger population: applying a systems approach,
IET-ITS(10), No. 1, 2016, pp. 25-31.
DOI Link 1602
geriatrics 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

Amin, M.G., Zhang, Y.D., Ahmad, F., Ho, K.C.D.,
Radar Signal Processing for Elderly Fall Detection: The future for in-home monitoring,
SPMag(33), No. 2, March 2016, pp. 71-80.
IEEE DOI 1603
Biomedical monitoring 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],
Human fall detection in videos via boosting and fusing statistical features of appearance, shape and motion dynamics on Riemannian manifolds with applications to assisted living,
CVIU(148), No. 1, 2016, pp. 111-122.
Elsevier DOI 1606
BibRef
Earlier:
Human fall detection via shape analysis on Riemannian manifolds with applications to elderly care,
ICIP15(3280-3284)
IEEE DOI 1512
Human fall detection 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
Target tracking BibRef

Park, M.[Myonghwa],
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

Senouci, B.[Benaoumeur], Charfim, I.[Imen], Heyrman, B.[Barthelemy], Dubois, J.[Julien], Miteran, J.[Johel],
Fast prototyping of a SoC-based smart-camera: A real-time fall detection case study,
RealTimeIP(12), No. 4, December 2016, pp. 649-662.
Springer DOI 1612
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

Ozcan, K.[Koray], Velipasalar, S.[Senem], Varshney, P.K.[Pramod K.],
Autonomous Fall Detection With Wearable Cameras by Using Relative Entropy Distance Measure,
HMS(47), No. 1, February 2017, pp. 31-39.
IEEE DOI 1702
cameras 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

Macků, L.[Lubomír], Matejíková, M.[Markéta],
Detection and Prevention of Seniors Falls,
Sensors(206), No. 11, November 2016, pp. 59-67.
HTML Version. 1705
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

Henriquez, P., Matuszewski, B.J., Andreu-Cabedo, Y., Bastiani, L., Colantonio, S., Coppini, G., D'Acunto, M., Favilla, R., Germanese, D., Giorgi, D., Marraccini, P., Martinelli, M., Morales, M.A., Pascali, M.A., Righi, M., Salvetti, O., Larsson, M., Strömberg, T., Randeberg, L., Bjorgan, A., Giannakakis, G., Pediaditis, M., Chiarugi, F., Christinaki, E., Marias, K., Tsiknakis, M.,
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, Three-dimensional displays, Videos, 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

Ferreira, B.V.[Bruno V.], Serejo, G.[Gerson], Ferreira, M.R.[Mylena R.], Ferreira, D.F.[Danilo F.], Cardoso, L.[Leon], Yoshidome, E.[Ewelton], Arruda, H.[Helder], Lira, W.[Wallace], Ferreira, Jr., J.[Jair], Carvalho, E.[Eduardo], Pessin, G.[Gustavo], Souza, C.R.B.[Cleidson R.B.],
Wearable computing for railway environments: proposal and evaluation of a safety solution,
IET-ITS(11), No. 6, August 2017, pp. 319-325.
DOI Link 1707
BibRef


Adhikari, K., Bouchachia, H., Nait-Charif, H.,
Activity recognition for indoor fall detection using convolutional neural network,
MVA17(81-84)
DOI Link 1708
Feature extraction, Monitoring, Neural networks, Organizations, Senior citizens, Sensitivity, Training BibRef

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

Vadivelu, S.[Somasundaram], Ganesan, S.[Sudakshin], Murthy, O.V.R.[O.V. Ramana], Dhall, A.[Abhinav],
Thermal Imaging Based Elderly Fall Detection,
CV4AC16(III: 541-553).
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

Iazzi, A.[Abderrazak], Rziza, M.[Mohammed], Thami, R.O.H.[Rachid Oulad Haj], Aboutajdine, D.[Driss],
A New Method for Fall Detection of Elderly Based on Human Shape and Motion Variation,
ISVC16(II: 156-167).
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
BibRef

Pramerdorfer, C.[Christopher], Planinc, R.[Rainer], Van Loock, M.[Mark], Fankhauser, D.[David], Kampel, M.[Martin], Brandstötter, M.[Michael],
Fall Detection Based on Depth-Data in Practice,
ACVR16(II: 195-208).
Springer DOI 1611
BibRef

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
BibRef

Sigurdsson, G.A.[Gunnar A.], Varol, G.[Gül], Wang, X.[Xiaolong], 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
BibRef

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

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
BibRef

Ayed, I.[Ines], Moyŕ-Alcover, B.[Biel], Martínez-Bueso, P.[Pau], Varona, J.[Javier], Ghazel, A.[Adel], Jaume-i-Capó, A.[Antoni],
Balance Clinical Measurement Using RGBD Devices,
AMDO16(125-134).
Springer DOI 1608
clinical prevention of falls. BibRef

Gu, I.Y.H.[Irene Yu-Hua], Kumar, D.P.[Durga Priya], Yun, Y.X.[Yi-Xiao],
Privacy-Preserving Fall Detection in Healthcare Using Shape and Motion Features from Low-Resolution RGB-D Videos,
ICIAR16(490-499).
Springer DOI 1608
BibRef

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
BibRef

Torres, C., Fragoso, V., Hammond, S.D., Fried, J.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

Rajabi, H., Nahvi, M.,
An intelligent video surveillance system for fall and anesthesia detection for elderly and patients,
IPRIA15(1-6)
IEEE DOI 1603
Gaussian processes 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

Lisowska, A., Wheeler, G., Inza, V.C., Poole, I.,
An Evaluation of Supervised, Novelty-Based and Hybrid Approaches to Fall Detection Using Silmee Accelerometer Data,
ACVR15(402-408)
IEEE DOI 1602
Accelerometers 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

Flores-Barranco, M.M.[Martha Magali], Ibarra-Mazano, M.A.[Mario-Alberto], Cheng, I.[Irene],
Accidental Fall Detection Based on Skeleton Joint Correlation and Activity Boundary,
ISVC15(II: 489-498).
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
BibRef

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
BibRef

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
BibRef

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
BibRef

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
BibRef

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
BibRef

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
BibRef

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
BibRef

Hernández, N.[Netzahualcóyotl], Favela, J.[Jesús],
Estimating the Perception of Physical Fatigue Among Older Adults Using Mobile Phones,
HBUI15(84-96).
Springer DOI 1511
BibRef

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],
Abnormal Behavioral Patterns Detection from Activity Records of Institutionalized Older Adults,
HBUI15(119-131).
Springer DOI 1511
BibRef

Lago, P.[Paula], Jiménez-Guarín, C.[Claudia], Roncancio, C.[Claudia],
Contextualized Behavior Patterns for Ambient Assisted Living,
HBUI15(132-145).
Springer DOI 1511
BibRef

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
BibRef

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
BibRef

Castellanos-Dominguez, G.[German],
Fall Detection Algorithm Based on Thresholds and Residual Events,
CIARP15(575-583).
Springer DOI 1511
BibRef

Trullo, R.[Roger], Martinez, D.[Duber],
Detecting Human Falls: A Vision-FSM Approach,
CAIP15(I:766-777).
Springer DOI 1511
BibRef

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
BibRef

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

Boulard, L., Baccaglini, E., Scopigno, R.,
Insights into the role of feedbacks in the tracking loop of a modular fall-detection algorithm,
VCIP14(406-409)
IEEE DOI 1504
geriatrics BibRef

Tayyub, J.[Jawad], Tavanai, A.[Aryana], Gatsoulis, Y.[Yiannis], 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
BibRef

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).
Springer DOI 1504
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
BibRef

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
BibRef

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
BibRef

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
BibRef

Zhang, Z.[Zhong], Conly, C.[Christopher], Athitsos, V.[Vassilis],
Evaluating Depth-Based Computer Vision Methods for Fall Detection under Occlusions,
ISVC14(II: 196-207).
Springer DOI 1501
BibRef

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

Demiröz, B.E.[Baris Evrim], Salah, A.A.[Albert Ali], Akarun, L.[Lale],
Coupling Fall Detection and Tracking in Omnidirectional Cameras,
HBU14(73-85).
Springer DOI 1411
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
BibRef

Kepski, M.[Michal], Kwolek, B.[Bogdan],
Person Detection and Head Tracking to Detect Falls in Depth Maps,
ICCVG14(324-331).
Springer DOI 1410
BibRef

Hung, D.H.[Dao Huu], Saito, H., Hsu, G.S.[Gee-Sern],
Detecting Fall Incidents of the Elderly Based on Human-Ground Contact Areas,
ACPR13(516-521)
IEEE DOI 1408
object detection BibRef

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

Jiang, M.[Mei], Chen, Y.[Yuyang], Zhao, Y.[Yanyun], Cai, A.[Anni],
A real-time fall detection system based on HMM and RVM,
VCIP13(1-6)
IEEE DOI 1402
geriatrics 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],
Daily Living Activities Recognition via Efficient High and Low Level Cues Combination and Fisher Kernel Representation,
CIAP13(I:431-441).
Springer DOI 1311
BibRef

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
BibRef

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
BibRef

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
BibRef

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
BibRef

Yamazaki, T.[Tatsuya],
Communicative robot interface for the ageing society,
ICARCV12(668-671).
IEEE DOI 1304
BibRef

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
BibRef

Planinc, R.[Rainer], Kampel, M.[Martin],
Combining Spatial and Temporal Information for Inactivity Modeling,
ICPR14(4234-4239)
IEEE DOI 1412
BibRef
And:
Robust Fall Detection by Combining 3D Data and Fuzzy Logic,
CDF12(II:121-132).
Springer DOI 1304
Hidden Markov models BibRef

Zhang, Z.[Zhong], Liu, W.H.[Wei-Hua], Metsis, V.[Vangelis], Athitsos, V.[Vassilis],
A viewpoint-independent statistical method for fall detection,
ICPR12(3626-3630).
WWW Link. 1302
BibRef

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).
WWW Link. 1302
BibRef

Wang, Y.[Yu], Kato, J.[Jien],
A distance metric learning based summarization system for nursery school surveillance video,
ICIP12(37-40).
IEEE DOI 1302
BibRef

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
BibRef

Chen, Y.T.[Yie-Tarng], Lin, Y.R.[You-Rong], Fang, W.H.[Wen-Hsien],
A Novel Shadow-Assistant Human Fall Detection Scheme Using a Cascade of SVM Classifiers,
SSSPR12(710-718).
Springer DOI 1211
BibRef

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
BibRef

Kepski, M.[Michal], Kwolek, B.[Bogdan],
Unobtrusive Fall Detection at Home Using Kinect Sensor,
CAIP13(457-464).
Springer DOI 1308
BibRef
Earlier:
Human Fall Detection by Mean Shift Combined with Depth Connected Components,
ICCVG12(457-464).
Springer DOI 1210
BibRef

Makantasis, K.[Konstantinos], Protopapadakis, E.[Eftychios], Doulamis, A.[Anastasios], Grammatikopoulos, L.[Lazaros], Stentoumis, C.[Christos],
Monocular Camera Fall Detection System Exploiting 3D Measures: A Semi-supervised Learning Approach,
ARTEMIS12(III: 81-90).
Springer DOI 1210
BibRef

Debard, G.[Glen], Karsmakers, P.[Peter], Deschodt, M.[Mieke], Vlaeyen, E.[Ellen], Dejaeger, E.[Eddy], Milisen, K.[Koen], Goedemé, T.[Toon], Vanrumste, B.[Bart], Tuytelaars, T.[Tinne],
Camera-Based Fall Detection on Real World Data,
WTFCV11(356-375).
Springer DOI 1210
BibRef

Meffre, A.[Alban], Collet, C.[Christophe], Lachiche, N.[Nicolas], Gançarski, P.[Pierre],
Real-Time Fall Detection Method Based on Hidden Markov Modelling,
ICISP12(521-530).
Springer DOI 1208
BibRef

Sokolova, M.V.[Marina V.], Fernández-Caballero, A.[Antonio],
Fuzzy Sets for Human Fall Pattern Recognition,
MCPR12(117-126).
Springer DOI 1208
BibRef

Pirsiavash, H.[Hamed], Ramanan, D.[Deva],
Detecting activities of daily living in first-person camera views,
CVPR12(2847-2854).
IEEE DOI 1208
BibRef

Humenberger, M.[Martin], Schraml, S.[Stephan], Sulzbachner, C.[Christoph], Belbachir, A.N.[Ahmed Nabil], Srp, A.[Agoston], Vajda, F.[Ferenc],
Embedded fall detection with a neural network and bio-inspired stereo vision,
ECVW12(60-67).
IEEE DOI 1207
BibRef

Dubey, R.[Rachit], Ni, B.B.[Bing-Bing], Moulin, P.[Pierre],
A Depth Camera Based Fall Recognition System for the Elderly,
ICIAR12(II: 106-113).
Springer DOI 1206
BibRef

Ni, B.B.[Bing-Bing], Wang, G.[Gang], Moulin, P.[Pierre],
RGBD-HuDaAct: A color-depth video database for human daily activity recognition,
ConDepth11(1147-1153).
IEEE DOI 1201
BibRef

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).
IEEE DOI 1207
BibRef

Belbachir, A.N.[Ahmed Nabil], Nowakowska, A.[Aneta], Schraml, S.[Stephan], Wiesmann, G.[Georg], Sablatnig, R.[Robert],
Event-driven feature analysis in a 4D spatiotemporal representation for ambient assisted living,
VECTaR11(1570-1577).
IEEE DOI 1201
BibRef

Qian, H.M.[Hui-Min], Mao, Y.B.[Yao-Bin], Xiang, W.[Wenbo], Wang, Z.Q.[Zhi-Quan],
Home environment fall detection system based on a cascaded multi-SVM classifier,
ICARCV08(1567-1572).
IEEE DOI 1109
BibRef

Belbachir, A.N.[Ahmed Nabil], Schraml, S.[Stephan], Nowakowska, A.[Aneta],
Event-driven stereo vision for fall detection,
ECVW11(78-83).
IEEE DOI 1106
BibRef

Appiah, K.[Kofi], Hunter, A.[Andrew], Waltham, C.[Christopher],
Low-power and efficient ambient assistive care system for elders,
ECVW11(97-102).
IEEE DOI 1106
BibRef

Evangelio, R.H.[Ruben Heras], Patzold, M.[Michael], Sikora, T.[Thomas],
A system for automatic and interactive detection of static objects,
POV11(27-32).
IEEE DOI 1101
See also Static Object Detection Based on a Dual Background Model and a Finite-State Machine. BibRef

Evangelio, R.H.[Ruben Heras], Keller, I.[Ivo], Sikora, T.[Thomas],
Multiple cue indexing and summarization of surveillance video,
AVSS13(371-376)
IEEE DOI 1311
Acceleration BibRef

Evangelio, R.H.[Ruben Heras], Senst, T.[Tobias], Sikora, T.[Thomas],
Detection of static objects for the task of video surveillance,
WACV11(534-540).
IEEE DOI 1101
I.e. a bag left behind. BibRef

Shoaib, M., Dragon, R., Ostermann, J.,
View-invariant Fall Detection for Elderly in Real Home Environment,
PSIVT10(52-57).
IEEE DOI 1011
BibRef

Hodlmoser, M.[Michael], Micusik, B.[Branislav], Kampel, M.[Martin],
Exploiting spatial consistency for object classification and pose estimation,
ICIP11(993-996).
IEEE DOI 1201
BibRef

Zweng, A.[Andreas], Zambanini, S.[Sebastian], Kampel, M.[Martin],
Introducing a Statistical Behavior Model into Camera-Based Fall Detection,
ISVC10(I: 163-172).
Springer DOI 1011
See also Performance evaluation of an improved relational feature model for pedestrian detection. BibRef

Zweng, A.[Andreas], Rittler, T.[Thomas], Kampel, M.[Martin],
Evaluation of Histogram-Based Similarity Functions for Different Color Spaces,
CAIP11(II: 455-462).
Springer DOI 1109
BibRef

Chen, Y.T.[Yie-Tarng], Lin, Y.C.[Yu-Ching], Fang, W.H.[Wen-Hsien],
A hybrid human fall detection scheme,
ICIP10(3485-3488).
IEEE DOI 1009
BibRef

Huang, Y.C.[Yi-Chang], Miaou, S.G.[Shaou-Gang], Liao, T.Y.[Tsung-Yen],
A Human Fall Detection System Using an Omni-Directional Camera in Practical Environments for Health Care Applications,
MVA09(455-).
PDF File. 0905
BibRef

Ober, A., Henrich, D.,
A Safe Fault Tolerant Multi-view Approach for Vision-Based Protective Devices,
AVSS10(17-25).
IEEE DOI 1009
BibRef

Malakuti, K.[Kaveh], Albu, A.B.[Alexandra Branzan],
Towards an Intelligent Bed Sensor: Non-intrusive Monitoring of Sleep Irregularities with Computer Vision Techniques,
ICPR10(4004-4007).
IEEE DOI 1008
BibRef

Cadavid, S.[Steven], Abdel-Mottaleb, M.[Mohamed],
Exploiting Visual Quasi-periodicity for Automated Chewing Event Detection Using Active Appearance Models and Support Vector Machines,
ICPR10(1714-1717).
IEEE DOI 1008
BibRef

Wu, P.[Pin], Hsieh, J.W.[Jun-Wei], Cheng, J.C.[Jiun-Cheng], Cheng, S.C.[Shyi-Chyi], Tseng, S.Y.[Shau-Yin],
Human Smoking Event Detection Using Visual Interaction Clues,
ICPR10(4344-4347).
IEEE DOI 1008
BibRef

Doulamis, A.D., Doulamis, N.D., Kalisperakis, I., Stentoumis, C.,
A Real-time Single-camera Approach For Automatic Fall Detection,
CloseRange10(xx-yy).
PDF File. 1006
BibRef

Snoek, J.[Jasper], Taati, B.[Babak], Eskin, Y.[Yulia], Mihailidis, A.[Alex],
Automatic segmentation of video to aid the study of faucet usability for older adults,
CVPR4HB10(63-70).
IEEE DOI 1006
BibRef

Xie, D.[Dan], Grupen, R.A.[Roderic A.], Hanson, A.R.[Allen R.],
Context-aware search using cooperative agents in a smart environment,
WACV09(1-6).
IEEE DOI 0912
Object search for elder care. BibRef

Ding, J.R.[Jiun-Ren],
Bed Status Detection for Elder-Care Center,
WSSIP09(1-4).
IEEE DOI 0906
BibRef

Puri, M.[Manika], Zhu, Z.W.[Zhi-Wei], Yu, Q.[Qian], Divakaran, A.[Ajay], Sawhney, H.[Harpreet],
Recognition and volume estimation of food intake using a mobile device,
WACV09(1-8).
IEEE DOI 0912
BibRef

Zouba, N.[Nadia], Bremond, F.[Francois], Thonnat, M.[Monique],
An Activity Monitoring System for Real Elderly at Home: Validation Study,
AVSS10(278-285).
IEEE DOI 1009
BibRef
Earlier:
Multisensor Fusion for Monitoring Elderly Activities at Home,
AVSBS09(98-103).
IEEE DOI 0909
BibRef

Zouba, N.[Nadia], Boulay, B.[Bernard], Bremond, F.[Francois], Thonnat, M.[Monique],
Monitoring Activities of Daily Living (ADLs) of Elderly Based on 3D Key Human Postures,
CogVis08(37-50).
Springer DOI 0805
Human Pose. Model video events from small set of postures. BibRef

Foroughi, H.[Homa], Rezvanian, A.[Alireza], Paziraee, A.[Amirhossien],
Robust Fall Detection Using Human Shape and Multi-class Support Vector Machine,
ICCVGIP08(413-420).
IEEE DOI 0812
BibRef

Hazelhoff, L.[Lykele], Han, J.G.[Jun-Gong], Bambang-Oetomo, S.[Sidarto], de With, P.H.N.[Peter H.N.],
Behavioral State Detection of Newborns Based on Facial Expression Analysis,
ACIVS09(698-709).
Springer DOI 0909
BibRef

Hazelhoff, L.[Lykele], Han, J.G.[Jun-Gong], de With, P.H.N.[Peter H.N.],
Video-Based Fall Detection in the Home Using Principal Component Analysis,
ACIVS08(xx-yy).
Springer DOI 0810
BibRef

Distante, C.[Cosimo], Leone, A.[Alessandro], Malcovati, P.[Piero],
A multi-sensor approach for People Fall Detection in home environment,
M2SFA208(xx-yy). 0810
BibRef

Rougier, C.[Caroline], Meunier, J.[Jean], St-Arnaud, A.[Alain], Rousseau, J.[Jacqueline],
Procrustes Shape Analysis for Fall Detection,
VS08(xx-yy). 0810
BibRef

Liao, W.H.[Wen-Hung], Yang, C.M.[Chien-Ming],
Video-based activity and movement pattern analysis in overnight sleep studies,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Vishwakarma, V.[Vinay], Mandal, C.[Chittaranjan], Sural, S.[Shamik],
Automatic Detection of Human Fall in Video,
PReMI07(616-623).
Springer DOI 0712
BibRef

Savogin, I., Scaioni, M., Fasoli, C.,
Portable monitoring and localization systems for disabled patients,
IEVM06(xx-yy).
PDF File. 0609
BibRef

Dedeoglu, Y.[Yigithan], Töreyin, B.U.[B. Ugur], Güdükbay, U.[Ugur], Çetin, A.E.[A. Enis],
Silhouette-Based Method for Object Classification and Human Action Recognition in Video,
CVHCI06(64-77).
Springer DOI 0605
BibRef

Töreyin, B.U.[B. Ugur], Dedeoglu, Y.[Yigithan], Çetin, A.E.[A. Enis],
HMM Based Falling Person Detection Using Both Audio and Video,
CVHCI05(211).
Springer DOI 0601
BibRef

Walther, D., Edgington, D.R., Koch, C.,
Detection and tracking of objects in underwater video,
CVPR04(I: 544-549).
IEEE DOI 0408
BibRef

Mori, T., Segawa, Y., Shimosaka, M., Sato, T.,
Hierarchical recognition of daily human actions based on Continuous Hidden Markov Models,
AFGR04(779-784).
WWW Link. 0411
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Lifelog .


Last update:Sep 25, 2017 at 16:36:46