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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Loza, A. Patricio, M.A. Garcia, J. Molina, J.M. |
| Copyright Year | 2008 |
| Description | Author affiliation: Appl. Artificial Intell. Group, Univ. Carlos III de Madrid, Colmenarejo (Patricio, M.A.; Garcia, J.; Molina, J.M.) || Dept. of Electr. & Electron. Eng., Univ. of Bristol, Bristol (Loza, A.) |
| Abstract | This paper investigates combinatorial and probabilistic approaches to real-time video target tracking. Of special interest are real-world scenarios, in which the presence of multiple targets and complex background pose a non-trivial challenge to automated trackers. Object tracking in an exemplary surveillance video sequence is accomplished by means of selected visual tracking techniques, based on two families of methods, combinatorial data association and Particle Filters. Based on the detailed analysis of the performance of the trackers tested, the advantages, complementary failure modes and computational requirements of each method have been identified. Taking into account the results obtained, the hybrid strategy for improved tracking performance is suggested, bringing together the best complementary features of the different tracking methods. |
| Starting Page | 125 |
| Ending Page | 131 |
| File Size | 332066 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781424422869 |
| DOI | 10.1109/ICARCV.2008.4795504 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-12-17 |
| Publisher Place | Vietnam |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Target tracking Surveillance Particle tracking Video sequences Particle filters Layout Cameras Robotics and automation State estimation Automatic control multiple target probabilistic combinatorial particle filters tracking surveillance real-time |
| Content Type | Text |
| Resource Type | Article |
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