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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Nater, F. Grabner, H. Jaeggli, T. van Gool, L. |
| Copyright Year | 2009 |
| Description | Author affiliation: Computer Vision Laboratory, ETH Zurich, Switzerland (Nater, F.; Grabner, H.; Jaeggli, T.; van Gool, L.) |
| Abstract | We present an approach for unusual event detection, based on a tree of trackers. At lower levels, the trackers are trained on broad classes of targets. At higher levels, they aim at more specific targets. For instance, at the root, a general blob tracker could operate which may track any object. The next level could already use information about human appearance to better track people. A further level could go after specific types of actions like walking, running, or sitting. Yet another level up, several walking trackers can be tuned to the gait of a particular person each. Thus, at each layer, one or more families of more specific trackers are available. As long as the target behaves according to expectations, a member of a higher up such family will be better tuned to the data than its parent tracker at a lower level. Typically, a better informed tracker performs more robustly. But in cases where unusual events occur and the normal assumptions about the world no longer hold, they loose their reliability. In such cases, a less informed tracker, not relying on what has now become false information, has a good chance of performing better. Such performance inversion signals an unusual event. Inversions between levels higher up represent deviations that are semantically more subtle than inversions lower down: for instance an unknown intruder entering a house rather than seeing a non-human target. |
| Starting Page | 1113 |
| Ending Page | 1120 |
| File Size | 3913790 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424444427 |
| DOI | 10.1109/ICCVW.2009.5457578 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-09-27 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Legged locomotion Computer vision Target tracking Event detection Conferences Laboratories Humans Streaming media Robustness Biomedical monitoring |
| Content Type | Text |
| Resource Type | Article |
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