Parallel Tracking of All Soccer Players by Integrating Detected Positions in Multiple View Images
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Semi-Supervised Adapted HMMs for Unusual Event Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Recognition of emergent human behaviour in a smart home: A data mining approach
Pervasive and Mobile Computing
Camera handoff with adaptive resource management for multi-camera multi-object tracking
Image and Vision Computing
An efficient Bayesian framework for on-line action recognition
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Kinematic self retargeting: A framework for human pose estimation
Computer Vision and Image Understanding
Use cases for abnormal behaviour detection in smart homes
ICOST'10 Proceedings of the Aging friendly technology for health and independence, and 8th international conference on Smart homes and health telematics
Fuzzy method to disclose behaviour patterns in a Tagged World
Expert Systems with Applications: An International Journal
Discovering Activities to Recognize and Track in a Smart Environment
IEEE Transactions on Knowledge and Data Engineering
Using association rule mining to discover temporal relations of daily activities
ICOST'11 Proceedings of the 9th international conference on Toward useful services for elderly and people with disabilities: smart homes and health telematics
Machine Recognition of Human Activities: A Survey
IEEE Transactions on Circuits and Systems for Video Technology
Human typical action recognition using gray scale image of silhouette sequence
Computers and Electrical Engineering
HBU'12 Proceedings of the Third international conference on Human Behavior Understanding
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To provide intelligent care and accompaniment for solitary seniors, it is the premise to recognize and understand their habits correctly, and at the same time the abnormal habit recognition is the important part of the habit understanding. At present, most of the researches are concentrated on behavior or abnormal behavior recognition, whereas the studies about the habit recognition are relatively scarce. In this paper, a method is proposed to recognize abnormal habits using key points' duration histogram combining with information provided by intelligent space. The contribution of this paper is as follows: 1. proposing a multi-camera positioning algorithm which improves the positioning accuracy by combining head location with posture recognition. 2. Proposing a new recognition algorithm which realizes the abnormal habits recognition effectively by clustering the data obtained from combining key points' duration histogram with the information of ISUS (intelligent space for understanding and service). Experiments show that the abnormal habit of seniors can be recognized properly using the methods proposed above.