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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Pelapur, R. Palaniappan, K. Seetharaman, G. |
| Copyright Year | 2012 |
| Abstract | Visual feature-based tracking systems need to adapt to variations in the appearance of an object and in the scene for robust performance. Though these variations may be small for short time steps, they can accumulate over time and deteriorate the quality of the matching process across longer intervals. Tracking in aerial imagery can be challenging as viewing geometry, calibration inaccuracies, complex ight paths and background changes combined with illumination changes, and occlusions can result in rapid appearance change of objects. Balancing appearance adaptation with stability to avoid tracking non-target objects can lead to longer tracks which is an indicator of tracker robustness. The approach described in this paper can handle affine changes such as rotation by explicit orientation estimation, scale changes by using a multiscale Hessian edge detector and drift correction by using segmentation. We propose an appearance update approach that handles the 'drifting' problem using this adaptive scheme within a tracking environment that is comprised of a rich feature set and a motion model. |
| Starting Page | 337 |
| Ending Page | 342 |
| File Size | 2611750 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467324991 |
| e-ISBN | 9780769547978 |
| DOI | 10.1109/AVSS.2012.92 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-09-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Adaptation models Target tracking Image edge detection Transforms Robustness Vehicles |
| Content Type | Text |
| Resource Type | Article |
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