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Content Provider | IEEE Xplore Digital Library |
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Author | Henriques, J.F. Caseiro, R. Batista, J. |
Copyright Year | 2011 |
Description | Author affiliation: Institute of Systems and Robotics, University of Coimbra, Portugal (Henriques, J.F.; Caseiro, R.; Batista, J.) |
Abstract | Multiple object tracking has been formulated recently as a global optimization problem, and solved efficiently with optimal methods such as the Hungarian Algorithm. A severe limitation is the inability to model multiple objects that are merged into a single measurement, and track them as a group, while retaining optimality. This work presents a new graph structure that encodes these multiple-match events as standard one-to-one matches, allowing computation of the solution in polynomial time. Since identities are lost when objects merge, an efficient method to identify groups is also presented, as a flow circulation problem. The problem of tracking individual objects across groups is then posed as a standard optimal assignment. Experiments show increased performance on the PETS 2006 and 2009 datasets compared to state-of-the-art algorithms. |
Starting Page | 2470 |
Ending Page | 2477 |
File Size | 2216349 |
Page Count | 8 |
File Format | |
ISBN | 9781457711015 |
ISSN | 15505499 |
e-ISBN | 9781457711022 |
DOI | 10.1109/ICCV.2011.6126532 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2011-11-06 |
Publisher Place | Spain |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Optimal matching Silicon Optimization Polynomials Joining processes Indexes Adaptation models |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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