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.,
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IEEE Top Reference.
0110
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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
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AVSBS03(87-92).
IEEE DOI
0310
BibRef
Karayiannis, N.B.,
Sami, A.,
Application of adaptive block matching in the extraction of temporal
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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
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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
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Aubert, D.[Didier],
Guichard, F.[Frédéric],
Bouchafa, S.[Samia],
Time-scale change detection applied to real-time abnormal stationarity
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Elsevier DOI
0405
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BibRef
Meniere, J.[Jerome],
Lefebure, M.[Martin],
Guichard, F.[Frederic],
Migliorini, C.[Christophe],
Method, system and device for detecting an object proximate
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US_Patent7,362,351, Apr 22, 2008
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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
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0606
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Earlier:
Novel region-based modeling for human detection within highly dynamic
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IEEE DOI
0408
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Eng, H.L.[How-Lung],
Kam, A.H.,
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Yau, W.Y.[Wei-Yun],
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Human detection and tracking within hostile aquatic environments,
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0310
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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
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OTCBVS04(130).
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0502
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Eng, H.L.[How-Lung],
Wang, J.X.[Jun-Xian],
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A bayesian framework for robust human detection and occlusion handling
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ICPR04(II: 257-260).
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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
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ICCV03(532-539).
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0311
BibRef
Eng, H.L.[How-Lung],
Toh, K.A.[Kar-Ann],
Yau, W.Y.[Wei-Yun],
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Recognition of Complex Human Behaviors in Pool Environment Using
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ISVC05(371-379).
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0512
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Eng, H.L.,
Toh, K.A.,
Yau, W.Y.,
Wang, J.,
DEWS: A Live Visual Surveillance System for Early Drowning Detection at
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0803
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Juang, C.F.,
Chang, C.M.,
Human Body Posture Classification by a Neural Fuzzy Network and Home
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0709
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Juang, C.F.,
Chang, C.M.,
Wu, J.R.,
Lee, D.,
Computer Vision-Based Human Body Segmentation and Posture Estimation,
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0901
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Yang, J.H.[Jeong-Hwa],
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McDonald, D.W.[David W.],
Activity Recognition for the Digital Home,
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0804
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Want, R.[Roy],
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Interactive Digital Signage,
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1202
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Chung, P.C.[Pau-Choo],
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0711
Behavior recognition; Duration HMM; Hierarchical HMM; Context
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0811
BibRef
Earlier: A1, A2, A3, A4, Only:
CRV06(5-5).
IEEE DOI
0607
Human motion analysis; Hidden Markov model; Gait analysis; Anomaly
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Automated video analysis; Machine learning; Biomedical analysis;
Stairs
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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
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Assistive technology; Decision theory; Human tracking; Particle
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Jeong, I.W.[Il-Woong],
Choi, J.[Jin],
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Seo, Y.H.[Yong-Ho],
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IEICE(E93-D), No. 7, July 2010, pp. 1745-1753.
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1008
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GE Healthcare's Smart Patient Room to Begin Data Collection,
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Ahmad, M.[Mohiuddin],
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0804
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And:
Recognizing human actions based on silhouette energy image and global
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FG08(1-6).
IEEE DOI
0809
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Earlier:
HMM-based Human Action Recognition Using Multiview Image Sequences,
ICPR06(I: 263-266).
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0609
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And:
Human Action Recognition Using Multi-View Image Sequences Features,
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Ahmad, M.[Mohiuddin],
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Contextual Information and Covariance Descriptors for People
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See also Multi-stage Sampling with Boosting Cascades for Pedestrian Detection in Images and Videos.
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Chung, P.C.[Pau-Choo],
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1104
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Earlier:
Robust Unattended and Stolen Object Detection by Fusing Simple
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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.
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Erratum:
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Compare to:
See also Tracking People by Learning Their Appearance. Use for sleeping human and pedestrians with clutter.
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Alam, M.R.,
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Jain, D.,
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1208
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1301
Events, not visual data. Electronic health records.
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1301
See also Video-based Gait Analysis By Silhouette Chamfer Distance And Kalman Filter.
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Forsyth, D.A.[David A.],
Technical Perspective: Understanding Pictures of Rooms,
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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
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Cook, D.J.,
Krishnan, N.C.,
Rashidi, P.,
Activity Discovery and Activity Recognition: A New Partnership,
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1307
home automation; behavioral pattern identification; Smart homes;
Activity recognition
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Lu, C.H.,
Ho, Y.C.,
Chen, Y.H.,
Fu, L.C.,
Hybrid User-Assisted Incremental Model Adaptation for Activity
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HMS(43), No. 5, 2013, pp. 421-436.
IEEE DOI
1311
Active learning
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Dawadi, P.N.,
Cook, D.J.,
Schmitter-Edgecombe, M.,
Automated Cognitive Health Assessment Using Smart Home Monitoring of
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SMCS(43), No. 6, 2013, pp. 1302-1313.
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1311
Dementia
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Chen, B.W.,
Chen, C.Y.,
Wang, J.F.,
Smart Homecare Surveillance System: Behavior Identification Based on
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Ambient intelligence
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Using Temporal Logic and Model Checking in Automated Recognition of
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Assisted living
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Hidden Markov models, Stochastic processes,
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A rule-based event detection system for real-life underwater domain,
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1402
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HMS(44), No. 1, February 2014, pp. 92-105.
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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],
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A context-aware approach for long-term behavioural change detection
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Context-aware
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Deboeverie, F.[Francis],
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SPIE(Newsroom), December 23, 2014.
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A low-resolution visual sensor network enables monitoring of elderly
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Hanca, J.[Jan],
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Lightweight real-time error-resilient encoding of visual sensor data,
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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.
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Accuracy
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Jain, R.C.[Ramesh C.],
Jalali, L.[Laleh],
Objective Self,
MultMedMag(21), No. 4, October 2014, pp. 100-110.
IEEE DOI
1502
healthcare monitoring
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Jalali, L.[Laleh],
Oh, H.[Hyungik],
Moazeni, R.[Ramin],
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Human Behavior Analysis from Smartphone Data Streams,
HBU16(68-85).
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Rosani, A.[Andrea],
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de Natale, F.G.B.[Francesco G.B.],
EventMask:
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Context
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FridgeNet: A Nutrition and Social Activity Promotion Platform for
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Aging
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Bridge: Mutual Reassurance for Autonomous and Independent Living,
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IEEE DOI
1506
Active appearance model
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Lee, E.,
Wearables for frail seniors,
Spectrum(52), No. 9, September 2015, pp. 25-25.
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1509
Resources_Tools.
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Zhang, H.,
Zhou, W.,
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Fuzzy Temporal Segmentation and Probabilistic Recognition of
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1509
Clustering algorithms
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Anton, S.,
Situation-Based Assess Tree for User Behavior Assessment in
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IEEE DOI
1509
Context
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Banerjee, T.[Tanvi],
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Elsevier DOI
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Scene understanding
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Robotic competitions
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Managing Wandering Risk in People With Dementia,
HMS(45), No. 6, December 2015, pp. 819-823.
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1512
Ambient assisted living
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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
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geriatrics
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Nguyen, T.[Thuong],
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Nonparametric discovery of movement patterns from accelerometer
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Movement intensity.
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MCNC: Multi-Channel Nonparametric Clustering from heterogeneous data,
ICPR16(3633-3638)
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Bayes methods, Computational modeling, Context, Context modeling,
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Ahmad, F.,
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Intro From the Guest Editors.
Assisted living
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Inertial Measurement Unit-Based Wearable Computers for Assisted
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IEEE DOI
1603
Assisted living
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Erden, F.,
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Alkar, A.Z.,
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Sensors in Assisted Living: A survey of signal and image processing
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IEEE DOI
1603
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Savazzi, S.,
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Kianoush, S.,
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Device-Free Radio Vision for Assisted Living: Leveraging wireless
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IEEE DOI
1603
Assisted living
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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
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IEEE DOI
1603
Assisted living
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Debes, C.,
Merentitis, A.,
Sukhanov, S.,
Niessen, M.,
Frangiadakis, N.,
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Monitoring Activities of Daily Living in Smart Homes:
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1603
Accelerometers
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Yun, Y.X.[Yi-Xiao],
Gu, I.Y.H.[Irene Yu-Hua],
Riemannian manifold-valued part-based features and geodesic-induced
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CVIU(161), No. 1, 2017, pp. 65-76.
Elsevier DOI
1708
Activity of daily living.
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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],
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Pediaditis, M.[Matthew],
Raccichini, G.[Giovanni],
Tsiknakis, M.[Manolis],
Wize Mirror: A smart, multisensory cardio-metabolic risk monitoring
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1606
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Marcon, M.[Marco],
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Toothbrush motion analysis to help children learn proper tooth
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CVIU(148), No. 1, 2016, pp. 34-45.
Elsevier DOI
1606
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Smart Toothbrushes:
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Target tracking
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Park, M.H.[Myong-Hwa],
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IJCVR(6), No. 3, 2016, pp. 261-266.
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Nejati, H.,
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Biological system modeling
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Complex activity recognition
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assisted living
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1702
Biomedical monitoring
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Jukan, A.[Admela],
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Smart Computing and Sensing Technologies for Animal Welfare:
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Animals play a profoundly important and intricate role in our lives
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Activity recognition, Aging, Hidden Markov models,
Intelligent agents, Intelligent sensors, Smart homes,
Activity recognition, ambient-assisted living (AAL),
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Chiang, Y.T.,
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1706
Data models, Feature extraction, Knowledge transfer,
Sensor phenomena and characterization, Smart homes, Testing,
Activity recognition (AR),
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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.,
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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,
Videos, Solid modeling,
3D face detection and tracking, 3D morphometric analysis,
Cardio-metabolic risk, breath analysis,
multimodal data integration, multispectral imaging,
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Serejo, G.[Gerson],
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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:
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IJGI(6), No. 10, 2017, pp. xx-yy.
DOI Link
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Active and Assisted Living. Where user stays and how long.
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Batalla, J.M.[Jordi Mongay],
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Secure Smart Homes: Opportunities and Challenges,
Surveys(50), No. 5, November 2017, pp. Article No 75.
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1712
Survey, Smart Homes. Sensors, security, future.
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Luo, Y.,
Lu, H.,
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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
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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
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Booth, K.E.C.,
Mohamed, S.C.,
Rajaratnam, S.,
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Robots in Retirement Homes: Person Search and Task Planning for a
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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
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Springer DOI
2301
BibRef
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Faraut, G.,
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An Integrated Framework for Binary Sensor Placement and Inhabitants
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IEEE DOI
1801
assisted living, data privacy, integer programming,
linear programming, sensor placement, wireless sensor networks,
smart home
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Fast Variable Structure Stochastic Automaton for Discovering and
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1802
Ambient assisted living, Automata, Convergence, Learning automata,
Noise measurement, Pattern recognition, Spatiotemporal phenomena,
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1804
Parkinson's disease, Triaxial accelerometer, Machine learning,
Feature reduction, Freezing of gait
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Emotion and Motivation in Cognitive Assistive Technologies for
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IEEE DOI
1804
Affective computing, Assistive technology, Cultural differences,
Decision making, Dementia, ACT, Affect Control Theory, BayesACT,
healthcare
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Jafari, R.,
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
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Jia, R.,
Jin, B.,
Jin, M.,
Zhou, Y.,
Konstantakopoulos, I.C.,
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Sangiovanni-Vincentelli, A.L.,
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Design Automation for Smart Building Systems,
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IEEE DOI
1810
building management systems, buildings (structures),
civil engineering computing, cyber-physical systems,
smart building
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A Multiview Multimodal System for Monitoring Patient Sleep,
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1810
Multi-stage noise shaping, Hidden Markov models,
Medical services, Feature extraction, Monitoring, Cameras, Videos,
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Machot, F.A.,
Mosa, A.H.,
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Activity Recognition in Sensor Data Streams for Active and Assisted
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1811
Activity recognition, Hidden Markov models, Smart homes,
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1906
Human activity analysis, Mobile robotics,
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Chen, P.C.[Pin-Chieh],
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Elderly well-being, Positive technology,
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Ambient assisted living, HMM, Behaviour recognition,
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Body pose, to enable automatic positioning.
Cameras, Hospitals, Calibration,
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Thermal comfort measurement, Thermal-depth images,
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An Empirical Approach to Modeling User-System Interaction Conflicts
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2011
Smart homes, Safety, Human computer interaction,
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Smart Home Personal Assistants: A Security and Privacy Review,
Surveys(53), No. 6, December 2020, pp. xx-yy.
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2103
Survey, Smart Home. Amazon Echo/Alexa, smart home, voice assistants,
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Wang, T.H.[Ting-Hui],
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sMRT: Multi-Resident Tracking in Smart Homes With Sensor
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2107
Smart homes, Layout, Hidden Markov models, Monitoring, Data models,
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Multi-Bernoulli Tracking Approach for Occupancy Monitoring of Smart
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2110
Service robotics, Incremental learning, Bioinspired robot learning
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Levels of Automation and Transparency: Interaction Design
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IEEE DOI
2112
Robots, Task analysis, Automation, Assistive devices,
Human-robot interaction, Assistive robots (ARs),
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Detecting the Presence of Electronic Devices in Smart Homes Using
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Expansion-Squeeze-Excitation Fusion Network for Elderly Activity
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2208
Older adults, Skeleton, Feature extraction, Fuses, Hair, Videos,
Task analysis, Elderly activity recognition, multi-modal fusion
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Cheng, J.[Junyi],
Zhang, X.F.[Xian-Feng],
Chen, X.[Xiao],
Ren, M.[Miao],
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Simultaneously-Collected Multimodal Lying Pose Dataset:
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2212
Pose estimation, Monitoring, Imaging, Hospitals, Benchmark testing,
Training, Human pose estimation, depth sensing, in-bed poses,
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Chen, K.Q.[Kai-Qi],
Liu, J.L.[Jia-Ling],
Chen, Q.Y.[Qin-Ying],
Wang, Z.H.[Zhen-Hua],
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Accurate Object Association and Pose Updating for Semantic SLAM,
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2212
For hospital robots.
Simultaneous localization and mapping, Semantics, Visualization,
Robots, Hospitals, Time measurement, Location awareness
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Her, P.[Paris],
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Dias, P.A.[Philipe A.],
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Uncertainty-Aware Gaze Tracking for Assisted Living Environments,
IP(32), 2023, pp. 2335-2347.
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2305
Uncertainty, Head, Assisted living, Gaze tracking, Videos,
Pose estimation, Neural networks, Machine learning, gaze tracking,
multi-camera assisted living scenario
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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
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IEEE DOI
2305
IoT for smart home.
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Liu, T.Z.[Ting-Zhuang],
He, X.Y.[Xin-Yu],
He, L.L.[Ling-Lu],
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A video drowning detection device based on underwater computer vision,
IET-IPR(17), No. 6, 2023, pp. 1905-1918.
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2305
computer vision, object detection, real-time systems, unsupervised learning
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Iqbal, S.[Shahrear],
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Beyond Smart Homes:
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Surveys(56), No. 2, September 2023, pp. 45.
DOI Link
2310
smart home, IoT, security issues, countermeasures,
smart healthcare, Smart aging care system
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Transferable Self-Supervised Instance Learning for Sleep Recognition,
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IEEE DOI
2310
BibRef
Zhang, Y.J.[Yi-Jian],
Tao, Q.Y.[Qian-Yi],
Yin, Y.[Yong],
A Lightweight Man-Overboard Detection and Tracking Model Using Aerial
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RS(16), No. 1, 2024, pp. xx-yy.
DOI Link
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Jeni, L.A.[László Attila],
de la Torre, F.[Fernando],
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2403
Action recognition, 3D motion capture,
Clinical in-bed monitoring, Diagnosis support, Epilepsy
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Mishra, P.K.[Pratik K.],
Ye, B.[Bing],
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Iaboni, A.[Andrea],
Mihailidis, A.[Alex],
Empirical Thresholding on Spatio-Temporal Autoencoders Trained on
Surveillance Videos in a Dementia Care Unit,
CRV23(265-272)
IEEE DOI
2406
Correlation coefficient, Surveillance, Training data, Psychology,
Cameras, Skeleton, Health and safety, agitation, dementia, autoencoder,
anomaly detection
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Cui, Y.C.[Yong-Cheng],
Tian, G.H.[Guo-Hui],
Jiang, Z.S.[Zheng-Song],
Zhang, M.Y.[Meng-Yang],
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An Active Task Cognition Method for Home Service Robot Using
Multi-Graph Attention Fusion Mechanism,
CirSysVideo(34), No. 6, June 2024, pp. 4957-4972.
IEEE DOI
2406
Task analysis, Cognition, Visualization, Semantics,
Feature extraction, Service robots, Multitasking, scene understanding
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Amraee, S.[Somaieh],
Galoaa, B.[Bishoy],
Goodwin, M.[Matthew],
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Multiple Toddler Tracking in Indoor Videos,
SmallData24(11-20)
IEEE DOI Code:
WWW Link.
2404
Measurement, Pediatrics, Streaming media, Feature extraction,
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Goel, A.[Akanksha],
Pathak, A.[Abha],
Tamrakar, P.[Poi],
Sharma, S.[Swati],
Thorat, P.[Pallavi],
Enhancing Patient Care and Monitoring Through AI and IoT in
Healthcare,
ICCVMI23(1-6)
IEEE DOI
2403
Data privacy, Ethics, Data security, Medical services,
Real-time systems, Internet of Things, Artificial intelligence,
Technology Privacy
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Jokar, F.[Fatemeh],
Azzopardi, G.[George],
Palotti, J.[Joao],
Towards Accurate and Efficient Sleep Period Detection Using Wearable
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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
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Shi-Ning, J.[Jin],
Yuan-Qing, Z.[Zhu],
Research on Pleasure Experience Design of Housekeeping APP for
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ICIVC22(963-967)
IEEE DOI
2301
Correlation, Aging, Internet, Older adults, Interviews,
middle-aged and elderly users, housekeeping APP, factor analysis,
experience pleasure
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Tanaka, K.[Kai],
Kudo, M.[Mineichi],
Kimura, K.[Keigo],
Sensor Data Simulation with Wandering Behavior for the Elderly Living
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ICPR22(885-891)
IEEE DOI
2212
Smart homes, Detectors, Reproducibility of results,
Probability distribution, Behavioral sciences, Planning
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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
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ICPR22(288-295)
IEEE DOI
2212
Sensors.
Wireless communication, Wireless sensor networks, Visualization,
Reliability engineering, Fractals, Sensors, Gabor filters
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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
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Embedded Intelligence for Safety and Security Machine Vision
Applications,
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2208
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2208
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Montoro-Lendínez, A.[Alicia],
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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).
Springer DOI
2208
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del Toro García, X.[Xavier],
Fernández-Bermejo, J.[Jesús],
Llumiguano, H.[Henry],
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Bolańos, C.[Cristina],
López, J.C.[Juan C.],
In-bed Posture and Night Wandering Monitoring Using Force-Sensing
Resistors,
VIAAL22(28-37).
Springer DOI
2208
BibRef
Santofimia, M.J.[Maria J.],
Villanueva, F.J.[Felix J.],
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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],
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Benvenuti, C.[Chiara],
Passera, M.[Mirko],
Falchi, F.[Fabrizio],
MOBDrone: A Drone Video Dataset for Man OverBoard Rescue,
CIAP22(II:633-644).
Springer DOI
2205
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Kiefer, B.[Benjamin],
Ott, D.[David],
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Leveraging Synthetic Data in Object Detection on Unmanned Aerial
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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,
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Ileri, K.,
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Karas, I.R.,
Development of IOT Enabled Global Tracking System and Mobile
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SmartCityApp21(287-290).
DOI Link
2201
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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
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SmartCity21(55-62).
DOI Link
2201
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Luo, Y.[Yiyue],
Li, Y.Z.[Yun-Zhu],
Foshey, M.[Michael],
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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).
Springer DOI
2106
BibRef
Codina-Filbŕ, J.[Joan],
Escalera, S.[Sergio],
Escudero, J.[Joan],
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Buch-Cardona, P.[Pau],
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Mobile ehealth Platform for Home Monitoring of Bipolar Disorder,
MMMod21(II:330-341).
Springer DOI
2106
BibRef
Garcia-Ceja, E.[Enrique],
Thambawita, V.[Vajira],
Hicks, S.A.[Steven A.],
Jha, D.[Debesh],
Jakobsen, P.[Petter],
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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
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
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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
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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
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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
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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
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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
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Grimaldo, A.I.[Ana I.],
Novak, J.[Jasminko],
User-Centered Visual Analytics Approach for Interactive and Explainable
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Springer DOI
1912
BibRef
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
BibRef
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
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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).
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1807
BibRef
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
BibRef
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
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Perrett, T.[Toby],
Damen, D.[Dima],
DDLSTM: Dual-Domain LSTM for Cross-Dataset Action Recognition,
CVPR19(7844-7853).
IEEE DOI
2002
BibRef
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
BibRef
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
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.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
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.
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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
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).
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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
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
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
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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
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
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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
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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
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Hernández, N.[Netzahualcóyotl],
Favela, J.[Jesús],
Estimating the Perception of Physical Fatigue Among Older Adults Using
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HBUI15(84-96).
Springer DOI
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Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Human Safety, Falling, Fall Detection, Home Care, Smart Home .