Segmentation for robust tracking in the presence of severe occlusion
Tracking an object in a sequence of images can fail due to partial occlusion or clutter. Robustness to occlusion can be increased by tracking the object as a set of "parts" such that not all of these are occluded at the same time. However, successful implementation of this idea hinges upon...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 13(2004), 2 vom: 24. Feb., Seite 166-78 |
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| Weitere Verfasser: | , |
| Format: | Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2004
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Comparative Study Evaluation Study Journal Article Research Support, U.S. Gov't, Non-P.H.S. Validation Study |
| Zusammenfassung: | Tracking an object in a sequence of images can fail due to partial occlusion or clutter. Robustness to occlusion can be increased by tracking the object as a set of "parts" such that not all of these are occluded at the same time. However, successful implementation of this idea hinges upon finding a suitable set of parts. In this paper we propose a novel segmentation, specifically designed to improve robustness against occlusion in the context of tracking. The main result shows that tracking the parts resulting from this segmentation outperforms both tracking parts obtained through traditional segmentations, and tracking the entire target. Additional results include a statistical analysis of the correlation between features of a part and tracking error, and identifying a cost function that exhibits a high degree of correlation with the tracking error |
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| Beschreibung: | Date Completed 12.10.2004 Date Revised 10.12.2019 published: Print Citation Status MEDLINE |
| ISSN: | 1941-0042 |