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


  • A. Ozturk Department of Mechatronics, Vocational School of Technical Sciences, Mus Alparslan University, Turkey
  • I. Cayiroglu Department of Mechatronics, Faculty of Engineering, Karabuk University, Turkey
Volume: 12 | Issue: 4 | Pages: 8872-8877 | August 2022 | https://doi.org/10.48084/etasr.5022


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.


Object Tracking, Object Detection, Computer Vision, SIFT, SSA


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How to Cite

A. Ozturk and I. Cayiroglu, “A Real-Time Application of Singular Spectrum Analysis to Object Tracking with SIFT”, Eng. Technol. Appl. Sci. Res., vol. 12, no. 4, pp. 8872–8877, Aug. 2022.


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