A method for real time tracking of non-rigid arbitrary objects is proposed in this study. The approach builds on and extends work on multidimensional color histogram based target representation, which is enhanced by spatial masking with a monotonically decreasing kernel profile prior to back-projection. The masking suppresses the influence of the background pixels and induces a spatially smooth target model representation suitable for gradient-based optimization. The main idea behind this approach is that an increase in the number of quantized feature spaces used to generate the target probability distribuition function during histogram back-projection can lead to improved target localization.
Target localization is performed using the recursive Mean shift procedure, which climbs the underlying density graidients of the discrete data to find the mode (peak) of the distribution.
Finally, the real time test cases, such as occlusion, target scale and orientation changes, varying illumination and background clutter, are demonstrated.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/2/12606102/index.pdf |
| Date | 01 May 2005 |
| Creators | Ozzaman, Gokhan |
| Contributors | Erkmen, Ismet |
| 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 METU campus |
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