Review: The use of pervasive sensing for behaviour profiling - a survey
Pervasive and Mobile Computing
Recognition of user activity sequences using distributed event detection
EuroSSC'07 Proceedings of the 2nd European conference on Smart sensing and context
From dialogue management to pervasive interaction based assistive technology
Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments
Hierarchical visual event pattern mining and its applications
Data Mining and Knowledge Discovery
Spatiotemporal analysis of human activities for biometric authentication
Computer Vision and Image Understanding
Survey on classifying human actions through visual sensors
Artificial Intelligence Review
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In this paper, we present a method for recognition of human activity as a series of actions from an image sequence. The difficulty with the problem is that there is a chicken-egg dilemma that each action needs to be extracted in advance for its recognition but the precise extraction is only possible after the action is correctly identified. In order to solve this dilemma, we use as many models as actions of our interest, and test each model against a given sequence to find a matched model for each action occurring in the sequence. For each action, a model is designed so as to represent any activity containing the action. The hierarchical hidden Markov model (HHMM) is employed to represent the models, in which each model is composed of a submodel of the target action and submodels which can represent any action, and they are connected appropriately. Several experimental results are shown.