Abstract
The continuous improvement in the level of sports competition has led to many recent research designs for providing easy and quick ways for athlete training. The aim behind this research is to present an adaptive hybrid non-rigid target tracking method by adopting (Mean-shift) and color histogram algorithm to process the characteristics of sports video. This work attempts in designing a tracking algorithm by implementing mean shift algorithm for tracking the object characteristics of sports objects. The experimental analysis presents the ideal effects of proposed approach in precision tracking. Mean shift algorithm uses the gradient method to iteratively calculate the extreme points of the probability density function using its characteristics of no parameters and fast pattern matching. In order to realize the tracking of human targets in sports videos, a tracking approach combining the mean shift process and the color histogram process is proposed. Using the statistical robustness of the mean shift process and the characteristics of rapid convergence along the direction of the density gradient, matching of the color histogram to the target shape is done. It solves the problem of variable target shape and high tracking complexity. The proposed method yields 96.04% precision and 97.10% accuracy value for tracking and recognition. The experimental outcomes obtained for the research provides the suitable evidence that the approach presented in this paper has an ideal effect.
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Yu, H., Sharma, A. & Sharma, P. Adaptive strategy for sports video moving target detection and tracking technology based on mean shift algorithm. Int J Syst Assur Eng Manag (2021). https://doi.org/10.1007/s13198-021-01128-5
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DOI: https://doi.org/10.1007/s13198-021-01128-5