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.
Mohamed, A. N., & Ali, M. M. (2014). MEAN SHIFT-BASED OBJECT TRACKING USING PROPER COLOR SPACE CHANNEL. JES. Journal of Engineering Sciences, 42(No 1), 199-215. doi: 10.21608/jesaun.2014.114301
MLA
Ahmed Nabil Mohamed; Mohamed Moness Ali. "MEAN SHIFT-BASED OBJECT TRACKING USING PROPER COLOR SPACE CHANNEL", JES. Journal of Engineering Sciences, 42, No 1, 2014, 199-215. doi: 10.21608/jesaun.2014.114301
HARVARD
Mohamed, A. N., Ali, M. M. (2014). 'MEAN SHIFT-BASED OBJECT TRACKING USING PROPER COLOR SPACE CHANNEL', JES. Journal of Engineering Sciences, 42(No 1), pp. 199-215. doi: 10.21608/jesaun.2014.114301
VANCOUVER
Mohamed, A. N., Ali, M. M. MEAN SHIFT-BASED OBJECT TRACKING USING PROPER COLOR SPACE CHANNEL. JES. Journal of Engineering Sciences, 2014; 42(No 1): 199-215. doi: 10.21608/jesaun.2014.114301
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