Metric distance transform for kernel based object tracking

An object tracking algorithm that uses the flexible kernels based on the normalized metric d_alpha distance transform for the mean shift procedure is proposed and tested. This replaces the more usual Epanechnikov kernel (E-kernel), improving target representation and localization without increasing the processing time, minimizing the similarity measure using the Bhattacharya coefficient. The target shape which defines the d_alpha distance transform is found either by regional segmentation or background-difference imaging, dependent on the nature of the video sequence. The algorithm is tested on several image sequences and shown to achieve robust and reliable frame-rate tracking.