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Content Provider | IEEE Xplore Digital Library |
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Author | Kumar, P. Dick, A. Brooks, M.J. |
Copyright Year | 2008 |
Description | Author affiliation: Sch. of Comput. Sci., Univ. of Adelaide, Adelaide, SA (Kumar, P.; Dick, A.; Brooks, M.J.) |
Abstract | This paper describes an approach to tracking multiple independently moving objects observed from moving cameras. The method addresses difficulties typically associated with tracking, including changes in background, parallax in the scene, arbitrary camera motion, object occlusions, cross-overs, and appearance changes. Using a bottom up approach, independently moving objects are detected in images acquired from a camera in free motion. These object detection results are then used in a top down particle filter framework to generate and evaluate object hypotheses. Integrating bottom up and top down approaches leads to more robust object detection, an improved object representation, and more effective generation and evaluation of target hypotheses. We demonstrate the effectiveness of the approach on real image sequences taken from hand-held cameras and from PETS 2005 dataset. |
Starting Page | 1 |
Ending Page | 6 |
File Size | 13532656 |
Page Count | 6 |
File Format | |
ISBN | 9781424437801 |
DOI | 10.1109/IVCNZ.2008.4762093 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2008-11-26 |
Publisher Place | New Zealand |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Tracking Particle Filter multiple cue Image sequences Bayesian methods multiple object Layout Bayesian Filter Object detection Moving Camera Cameras Motion detection Particle filters Robustness Positron emission tomography |
Content Type | Text |
Resource Type | Article |
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