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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chuohao Yeo Ahammad, P. Ramchandran, K. Sastry, S.S. |
| Copyright Year | 1991 |
| Abstract | We present a compressed domain scheme that is able to recognize and localize actions at high speeds. The recognition problem is posed as performing an action video query on a test video sequence. Our method is based on computing motion similarity using compressed domain features which can be extracted with low complexity. We introduce a novel motion correlation measure that takes into account differences in motion directions and magnitudes. Our method is appearance-invariant, requires no prior segmentation, alignment or stabilization, and is able to localize actions in both space and time. We evaluated our method on a benchmark action video database consisting of six actions performed by 25 people under three different scenarios. Our proposed method achieved a classification accuracy of 90%, comparing favorably with existing methods in action classification accuracy, and is able to localize a template video of 80 x 64 pixels with 23 frames in a test video of 368 x 184 pixels with 835 frames in just 11 s, easily outperforming other methods in localization speed. We also perform a systematic investigation of the effects of various encoding options on our proposed approach. In particular, we present results on the compression-classification tradeoff, which would provide valuable insight into jointly designing a system that performs video encoding at the camera front-end and action classification at the processing back-end. |
| Sponsorship | IEEE Circuits and Systems Society |
| Starting Page | 1006 |
| Ending Page | 1015 |
| Page Count | 10 |
| File Size | 1553665 |
| File Format | |
| ISSN | 10518215 |
| Volume Number | 18 |
| Issue Number | 8 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-08-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Cameras Testing Performance evaluation Video sequences Encoding Motion measurement Databases Video surveillance Video coding Video signal processing video signal processing Action recognition compressed domain processing real-time video surveillance video coding Compressed domain processing Real-time video surveillance |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Media Technology |
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