MEAN SHIFT-BASED OBJECT TRACKING USING PROPER COLOR SPACE CHANNEL | ||||
| JES. Journal of Engineering Sciences | ||||
| Article 12, Volume 42, No 1, January and February 2014, Page 199-215 PDF (576.69 K) | ||||
| Document Type: Research Paper | ||||
| DOI: 10.21608/jesaun.2014.114301 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Ahmed Nabil Mohamed1; Mohamed Moness Ali2 | ||||
| 1Assistant Lecturer, Department of Computer and Information Systems, Sadat Academy | ||||
| 2Professor, Department of Computers and Systems, Engineering Faculty, Minia University | ||||
| Abstract | ||||
| Color features show robustness against many variations such as translation, rotation, viewpoint change, partial occlusion, low resolution, pose variations, etc. Thus, they are considered effective cues for object representation and are widely employed for visual tracking. Mean shift algorithm is a robust non parametric technique that is used for estimating the gradient of a density function. It is employed widely as a fast and robust object tracker that can utilize any feature space such as the color space. In this article, we present a simple but rather effective enhancement to the mean shift algorithm to distinguish an object from its background by using a proper color space channel that is selected according to the region of interest. | ||||
| Keywords | ||||
| Color Space; Histogram; Mean Shift; Object Tracking | ||||
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