Improving the Performance of Video Tracking Using SVM

Ms. G.Anusha; Mrs. E. Golden Julie

doi:https://doi.org/10.14445/22315381/IJETT-V11P226

Research Article | Open Access | Download PDF

Volume 11 | Number 1 | Year 2014 | Article Id. IJETT-V11P226 | DOI : https://doi.org/10.14445/22315381/IJETT-V11P226

Improving the Performance of Video Tracking Using SVM

Ms. G.Anusha , Mrs. E. Golden Julie

Citation :

Ms. G.Anusha , Mrs. E. Golden Julie, "Improving the Performance of Video Tracking Using SVM," International Journal of Engineering Trends and Technology (IJETT), vol. 11, no. 1, pp. 133-139, 2014. Crossref, https://doi.org/10.14445/22315381/IJETT-V11P226

Abstract

Object tracking is the process of separating the moving object from the video sequences. Tracking is essentially a matching problem in object tracking. In order to avoid this matching problem, object recognition is done on the tracked object. . Kalman filter cannot separate the moving object in multiple object tracking so we use background separation techniques. . Background separation algorithm separate moving object from the background based on white and black pixels .Support Vector Machines classifier is used to recognize the tracked object. SVM classifier are supervised learning that associates with machine learning algorithm that analyse and recognize the data used for classification.

Keywords

Object tracking, Support Vector Machines, Background separation, Gabor filter, Object recognition.

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