Abstract
Video processing is a most challenging research area among image processing. It has made its mark over the world by the rapid development of technology in various fields. Extending the study in the area of sports video digitization, proposed methodology initiated the novel approach on Asian game that is ‘Kabaddi’. It is a team game, in which we emphasize on half of the court. This paper proposes a content analysis of kabaddi game includes both foreground and back ground annotation. Player classification, detection and tracking by dominant Color-based Feature Extraction (CFE). Blob generation for each player with consequences of team has performed using accumulation array with grid based transaction and Centroid Region Of Interest (CROI). Then by applying the grids over the play court, line detection and labeling is done by Hough Grid Transformation (HGT) method. Algorithms are implemented on MATALAB tool and tested on self developed videos having 535 frame set videos clips for privileged accuracy in the obliged aspects. By examining the results, proposed methodology can be referred in the Kabaddi tournaments for game annotation and player performance analysis.
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Acknowledgment
There is no legal data set available for the research on the kabaddi game, since have created our own data set. This was done with the guidance of Dr.Rajakumar Malipatil, (Registrar Evaluator) Director of Physical Education Department (PED), Akkamahadevi Woman’s University Viajayapur (AWU), for the right ground truth examination and played by AWU-PED International Kabaddi players. Another data set was created in Mangalore University by taking official permission from the parent university and Alva’s PED Director. We are grateful to both PED team for their supervision, which made possible to develop required data set on as per the required research criterions.
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Makandar, A., Mulimani, D. (2019). Video Annotation and Player Classification Using Hough-Grid Transformation (HGT) Method. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1035. Springer, Singapore. https://doi.org/10.1007/978-981-13-9181-1_30
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DOI: https://doi.org/10.1007/978-981-13-9181-1_30
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