《Kinect体感程式设计入门》.pdfVIP

Computer Vision and Image Understanding 96 (2004) 129–162 /locate/cviu Video-based event recognition: activity representation and probabilistic recognition methodsq * 1 Somboon Hongeng , Ram Nevatia, Francois Bremond Institute for Robotics and Intelligent Systems, University of Southern California, Los Angeles, CA 90089, USA Received 15 March 2002; accepted 2 February 2004 Available online 13 August 2004 Abstract We present a new representation and recognition method for human activities. An activity is considered to be composed of action threads, each thread being executed by a single actor. A single-thread action is represented by a stochastic finite automaton of event states, which are recognized from the characteristics of the trajectory and shape of moving blob of the actor using Bayesian methods. A multi-agent event is composed of several action threads related by temporal constraints. Multi-agent events are recognized by propagating the constraints and likelihood of event threads in a temporal logic network. We present results on real-world data and performance characterization on perturbed data. 2004 Elsevier Inc. All rights reserved. Keywords: Video-based event detection; Event mining; Activity recognition q This research was supported in part by the Advanced Research and Development Activity of the U.S. Government under Contract No. MDA-908-00-C-0036. * Correspondence to: KOGS, FB Informatik, University of Hamburg, Vogt-Koelln-Str. 30, D-22527 Hamburg, Germany. E-mail addresses: hongeng@ (S. Hongeng), nevatia@ (R.