Shots Classification for Basketball Video Based on NERFC-Means Clustering
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| Title | Shots Classification for Basketball Video Based on NERFC-Means Clustering |
| Authors | |
| Abstract | shots classification is the fundamental for sports video annotation. This paper uses non-supervised method to cluster the shots into defined classes (in-play, close-up and free-throw) based on the low-level features of the image (the main color and the histogram). Specifically, we apply the None Euclidean Relational Fuzzy C-means (NERFCM) to cluster the shots after comparing the four Fuzzy C-means and extracting the low-level features of the frames. Experiments prove its efficiency and sensitivity. |
| Publisher | ACADEMY PUBLISHER |
| Date | 2011-07-01 |
| Source | Journal of Computers Vol 6, No 7 (2011) |
| Rights | Copyright © ACADEMY PUBLISHER - All Rights Reserved.To request permission, please check out URL: http://www.academypublisher.com/copyrightpermission.html. |