Comparative Performance Evaluation of Three Object Tracking Methods

Provided by: International Journal of Emerging Technology and Advanced Engineering (IJETAE)
Topic: Software
Format: PDF
Object tracking is the process of locating a moving object in the consecutive video frames. It is a challenging problem in the field of computer vision, automated surveillance, traffic monitoring, augmented reality, and object based video compression, etc. In this paper three techniques such as kernel based tracking using color histogram, tracking using segmentation and covariance feature based mean shift tracking algorithm have been applied for different challenging situations. Experimental results revels that the histogram based method is efficient in terms of computation time and covariance tracker is better in terms of detection rate.

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