Improving the Performance of Video Tracking Using SVM

Journal Title: INTERNATIONAL JOURNAL OF ENGINEERING TRENDS AND TECHNOLOGY - Year 2014, Vol 11, Issue 3

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.

Authors and Affiliations

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

Keywords

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  • EP ID EP142211
  • DOI -
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How To Cite

Ms. G. Anusha, Mrs. E. Golden Julie (2014). Improving the Performance of Video Tracking Using SVM. INTERNATIONAL JOURNAL OF ENGINEERING TRENDS AND TECHNOLOGY, 11(3), 133-139. https://europub.co.uk/articles/-A-142211