Descriptive temporal template features for visual motion recognition
Pattern Recognition Letters
Object relevance weight pattern mining for activity recognition and segmentation
Pervasive and Mobile Computing
Incorporating duration information in activity recognition
KSEM'10 Proceedings of the 4th international conference on Knowledge science, engineering and management
Activity discovery using compressed suffix trees
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
Ambient Assisted Living system for in-home monitoring of healthy independent elders
Expert Systems with Applications: An International Journal
Incremental behavior modeling and suspicious activity detection
Pattern Recognition
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We describe an algorithm for dining activity analysis in a nursing home. Based on several features, including motion vectors and distance between moving regions in the subspace of an individual person, a hidden Markov model is proposed to characterize different stages in dining activities with certain temporal order. Using HMM model, we are able to identify the start (and ending) of individual dining events with high accuracy and low false positive rate. This approach could be successful in assisting caregivers in assessments of resident's activity levels over time.