NDLI: Representation and optimal recognition of human activities

Content Provider	IEEE Xplore Digital Library
Author	Somboon Hongeng Bremond, F. Nevatia, R.
Copyright Year	2000
Description	Author affiliation: Inst. for Robotics & Intelligent Syst., Univ. of Southern California, Los Angeles, CA, USA (Somboon Hongeng)
Abstract	Towards the goal of realizing a generic automatic human activity recognition system, a new formalism is proposed. Activities are described by a chained hierarchical representation using three type of entities: image features, mobile object properties and scenarios. Taking image features of tracked moving regions from an image sequence as input, mobile object properties are first computed by specific methods while noise is suppressed by statistical methods. Scenarios are recognized from mobile object properties based on Bayesian analysis. Several scenarios are recognized by an algorithm using a probabilistic finite-state automaton (a variant of structured HMM). A demonstration of the optimality of this recognition method is discussed. Finally, the validity and the effectiveness of our approach is demonstrated on both real-world and perturbed data.
Starting Page	818
Ending Page	825
File Size	229020
Page Count	8
File Format	PDF
ISBN	0769506623
ISSN	10636919
DOI	10.1109/CVPR.2000.855905
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-06-15
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humans Image sequences Image recognition Intelligent robots Mobile computing Bayesian methods Automata Computer vision Electrical capacitance tomography Event detection
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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