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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sultani, W. Jin Young Choi |
| Copyright Year | 2010 |
| Abstract | We present a novel approach for detecting and localizing abnormal traffic using intelligent driver model. Specifically, we advect particles over video sequence. By treating each particle as a car, we compute driver behavior using intelligent driver model. The behaviors are learned using latent dirichlet allocation and frames are classified as abnormal using likelihood threshold criteria. In order to localize the abnormality; we compute spatial gradients of behaviors and construct Finite Time Lyaponov Field. Finally the region of abnormality is segmented using watershed algorithm. The effectiveness of proposed approach is validated using videos from stock footage websites. |
| Starting Page | 324 |
| Ending Page | 327 |
| File Size | 1015033 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424475421 |
| ISSN | 10514651 |
| e-ISBN | 9781424475414 |
| DOI | 10.1109/ICPR.2010.88 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-08-23 |
| Publisher Place | Turkey |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Driver circuits Computational modeling Image motion analysis Computer vision Accidents Roads Video sequences |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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