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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Mixed-State Models for Nonstationary Multiobject Activities | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 65989 14 pages doi 10.1155 2007 65989 Research Article Mixed-State Models for Nonstationary Multiobject Activities Naresh P Cuntoor and Rama Chellappa Department of Electrical and Computer Engineering Center for Automation Research University of Maryland A. y Williams Building College Park MD 20742 USA Received 13 June 2006 Revised 20 October 2006 Accepted 30 October 2006 Recommended by Francesco G. B. De Natale We present a mixed-state space approach for modeling and segmenting human activities. The discrete-valued component of the mixed state represents higher-level behavior while the continuous state models the dynamics within behavioral segments. A basis of behaviors based on generic properties of motion trajectories is chosen to characterize segments of activities. A Viterbi-based algorithm to detect boundaries between segments is described. The usefulness of the proposed approach for temporal segmentation and anomaly detection is illustrated using the TSA airport tarmac surveillance dataset the bank monitoring dataset and the UCF database of human actions. Copyright 2007 N.P. Cuntoor and R. Chellappa. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION Modeling complex activities involves extracting spatiotemporal descriptors associated with objects moving in a scene. It is natural to think of activities as a sequence of segments in which each segment possesses coherent motion properties. There exists a hierarchical relationship extending from observed features to higher-level behaviors of moving objects. Features such as motion trajectories and optical flow are continuous-valued variables whereas behaviors such as start stop split merge and move along a straight line are .