In this paper a fast, reliable and robust algorithm against occlusion for visual tracking of a pre-defined target in sequence images based on adapting template of target edges with search space edges is presented. At first, target window is specified by user and then th
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In this paper a fast, reliable and robust algorithm against occlusion for visual tracking of a pre-defined target in sequence images based on adapting template of target edges with search space edges is presented. At first, target window is specified by user and then the proposed algorithm determines an appropriate model for the target by choosing the best edges of the target window. Moreover, to increase robustness against occlusion, target model has been divided into four equal divisions and by performing a logical AND between the template of each division edges and search space edges and then by counting its non-zero pixels, resemblance matrix for each division of target is obtained. In a case that values of the resemblance matrix are less than values of threshold matrix, the desired division is considered occluded and then by taking the effects of non-occluded divisions into account, the exact location of the target in each frame is determined. In the tracking values, in case of appropriate condition respect to background condition, the model of target edges is updated. Selecting dominant edges, multi dividing and updating the target template, has resulted in increasing the robustness of the algorithm against some vital challenges such as changing in ambient and target light, and occurring occlusion over target. The simplicity of this algorithm has provided the possibility of real-time implementation in OpenCV environment using C language, that achieves averagely to more than 60 frames per second for a computer with 2.6 GHz CPU and 4 GB RAM. Moreover, comparing the results of the proposed algorithm to other algorithms, revealed a higher speed and greater reliability.
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