People Tracking using Color Control Points and Skin Color

This paper presents a new approach to be used for people detection and tracking in image sequences based on color control points and skin color modeling. This method aims to track these people in complex situations such as players on a soccer field. Each person in the image is represented by several control points which are obtained using a color version of the Harris algorithm detector. Each control point is characterized by the local appearance which is a vector of local characteristics. Then we determine the rules that define the skin regions in three different color spaces such as RGB, HSV and YCbCr, and we apply these rules to our images to segment skin regions. Using a set of control points and skin regions allows us to track a person by matching control points based on the measure of ZNCC correlation «Zero mean Normalized Cross Correlation». The simulations and experimental results show the robustness of our algorithms in terms of stability and convergence. Performance is illustrated by some examples. Thus, our method fits well with the noise conditions.

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