A Real-Time Application of Singular Spectrum Analysis to Object Tracking with SIFT

Abstract

This study combined SIFT and SSA to propose a novel algorithm for real-time object tracking. The proposed algorithm utilizes an intermediate fixed-size buffer and a modified SSA algorithm. Since the complete reconstruction step of the SSA algorithm was unnecessary, it was considerably simplified. In addition, the execution time of a Matlab implementation of the SSA algorithm was compared with a respective C++ implementation. Moreover, the performance of the two different matching algorithms in the detection, the FlannBasedMatcher and Brute-Force matcher algorithms of the OpenCV library, was compared.