Moving Basket Ball Detection and Tracking System by Different Approaches
G. Simi Margarat1, S. Sivasubramanian2
1G. Simi Margarat, Reseach Scholar, Department of Computer Science and Engineering, Bharath University, Chennai (Tamil Nadu), India.
2S. Sivasubramanian, Principal & Professor, Mohamed Sathak College of Engineering, Chennai (Tamil Nadu), India.
Manuscript received on 14 December 2018 | Revised Manuscript received on 26 December 2018 | Manuscript Published on 24 January 2019 | PP: 270-278 | Volume-7 Issue-4S2 December 2018 | Retrieval Number: Es2066017519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper presents the detail investigation on different methods used for the basket ball detection and tracking. The object detection and tracking with high performance ratio for video object detection and tracking is achieved in the methods investigated. But most of the methods suffer from computational complexity. The reduction of complexity can happen at any stages of the ball tracking like preprocessing, segmentation, feature extraction, background subtraction and hole filling. The methods investigated in this paper are trajectory based ball-detection and tracking method, region growing algorithm, PSO algorithm and Mean Shift algorithm with HSV color space and texture features. Detail investigation on the approaches, implementation issues and future trends are presented.
Keywords: Basket Ball Detection, Tracking, Trajectory, Particle Swarm Optimization, Mean Shift Algorithm, Segmentation.
Scope of the Article: System Integration