Multiple Objects Tracking with Location Matching and Adaptive Windowing Based on SIFT Algorithm
Keywords:
Multiple Objects SIFT Location Matching Adaptive WindowingAbstract
Multiple objects tracking have been an interesting research topic in computer vision and its related fields. It is a very important work to detect exactly the consecutive multiple objects and to track them effectively. In this paper, we propose a robust tracking system that utilizes several techniques such as multiple objects detection from multi-lateral histogram, location matching of the feature descriptor from Scale Invariant Feature Transform (SIFT) algorithm, and adaptive windowing for effective tracking. In order to analyze the performance of the proposed tracking system three videos were tested that multiple objects show various types of appearances. Experimental results reveal that the proposed system has an advanced tracking ability in complicated circumstances.
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