An algorithm for tracking single visual targets is developed in this study.
Feature detection is the necessary and appropriate image processing technique for
this algorithm. The main point of this approach is to use the data supplied by the
feature detection as the observation from a group of targets having similar motion
dynamics. Therefore a single visual target is regarded as a group of multiple targets.
Accurate data association and state estimation under clutter are desired for this
application similar to other multi-target tracking applications. The group tracking
approach is used with the well-known probabilistic data association technique to
cope with data association and estimation problems. The applicability of this
method particularly for visual tracking and for other cases is also discussed.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/4/1056100/index.pdf |
| Date | 01 January 2003 |
| Creators | Arslan, Ali Erkin |
| Contributors | Demirekler, Mubeccel |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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