Performance Comparison of KLT and CAMSHIFT Algorithms for Video Object Tracking

  • Prateek SharmaEmail author
  • Pranjali M. Kokare
  • Maheshkumar H. KolekarEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 524)


Human detection and tracking is one of the most crucial tasks in video analysis. We can find its applications in areas like video surveillance, augmented reality, traffic supervision. KLT and CAMSHIFT are two popular algorithms for this task. In this paper, we present a comparison of their performance in different scenarios. As a result, this paper provides concrete statistics to choose an appropriate algorithm for tracking, given the nature of the objects and surrounding. Our experiments show that KLT algorithm is advantageous for crowded scenes, whereas CAMSHIFT performs better for tracking a specific target. Based on our analysis, we conclude that KLT algorithm performs more efficiently than CAMSHIFT algorithm for video object tracking.


Video object tracking KLT CAMSHIFT Video surveillance system 


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Indian Institute of Technology PatnaBihta, PatnaIndia

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