Abnormal Event Detection via Multikernel Learning for Distributed Camera Networks
Distributed camera networks play an important role in public security surveillance. Analyzing video sequences from cameras set at different angles will provide enhanced performance for detecting abnormal events. In this paper, an abnormal detection algorithm is proposed to identify unusual events ca...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-09-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/989450 |
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| _version_ | 1832559153268129792 |
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| author | Tian Wang Jie Chen Paul Honeine Hichem Snoussi |
| author_facet | Tian Wang Jie Chen Paul Honeine Hichem Snoussi |
| author_sort | Tian Wang |
| collection | DOAJ |
| description | Distributed camera networks play an important role in public security surveillance. Analyzing video sequences from cameras set at different angles will provide enhanced performance for detecting abnormal events. In this paper, an abnormal detection algorithm is proposed to identify unusual events captured by multiple cameras. The visual event is summarized and represented by the histogram of the optical flow orientation descriptor, and then a multikernel strategy that takes the multiview scenes into account is proposed to improve the detection accuracy. A nonlinear one-class SVM algorithm with the constructed kernel is then trained to detect abnormal frames of video sequences. We validate and evaluate the proposed method on the video surveillance dataset PETS. |
| format | Article |
| id | doaj-art-8c5aa498c84a4b7286334023291716b4 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-8c5aa498c84a4b7286334023291716b42025-02-03T01:30:42ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-09-011110.1155/2015/989450989450Abnormal Event Detection via Multikernel Learning for Distributed Camera NetworksTian Wang0Jie Chen1Paul Honeine2Hichem Snoussi3 School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China CIAIC, School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China Institut Charles Delaunay, LM2S, UMR STMR 6279 CNRS, University of Technology of Troyes, 10004 Troyes, France Institut Charles Delaunay, LM2S, UMR STMR 6279 CNRS, University of Technology of Troyes, 10004 Troyes, FranceDistributed camera networks play an important role in public security surveillance. Analyzing video sequences from cameras set at different angles will provide enhanced performance for detecting abnormal events. In this paper, an abnormal detection algorithm is proposed to identify unusual events captured by multiple cameras. The visual event is summarized and represented by the histogram of the optical flow orientation descriptor, and then a multikernel strategy that takes the multiview scenes into account is proposed to improve the detection accuracy. A nonlinear one-class SVM algorithm with the constructed kernel is then trained to detect abnormal frames of video sequences. We validate and evaluate the proposed method on the video surveillance dataset PETS.https://doi.org/10.1155/2015/989450 |
| spellingShingle | Tian Wang Jie Chen Paul Honeine Hichem Snoussi Abnormal Event Detection via Multikernel Learning for Distributed Camera Networks International Journal of Distributed Sensor Networks |
| title | Abnormal Event Detection via Multikernel Learning for Distributed Camera Networks |
| title_full | Abnormal Event Detection via Multikernel Learning for Distributed Camera Networks |
| title_fullStr | Abnormal Event Detection via Multikernel Learning for Distributed Camera Networks |
| title_full_unstemmed | Abnormal Event Detection via Multikernel Learning for Distributed Camera Networks |
| title_short | Abnormal Event Detection via Multikernel Learning for Distributed Camera Networks |
| title_sort | abnormal event detection via multikernel learning for distributed camera networks |
| url | https://doi.org/10.1155/2015/989450 |
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