A Novel Hybrid Adaptive Filter to Improve Video Keyframe Clustering to Support Event Resolution in Cricket Videos
S. C. Premaratne1, K. L. Jayaratne2, P. Sellappan3
1S. C. Premaratne, Department of Information Technology, University of Moratuwa.
2K. L. Jayaratne, Department of Computing, University of Colombo Sri Lanka.
3P. Sellappan, Department of Science and Technology, Malaysia University of Science and Technology, MUST.
Manuscript received on 27 September 2019 | Revised Manuscript received on 09 November 2019 | Manuscript Published on 22 November 2019 | PP: 22-30 | Volume-8 Issue-6S3 September 2019 | Retrieval Number: F10050986S319/19©BEIESP | DOI: 10.35940/ijeat.F1005.0986S319
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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: Automated summary generation of sports videos poses many challenges of detecting exciting events of a game. In our research, we focus on the table of content-based video summarization for cricket videos to facilitate efficient indexing of cricket events. Initially, we have identified event boundaries accurately to detect the event start and end points. To distinguish the different types of events, we need to analyze the sequence of the camera focus area. By observing the characteristics, we have categorized the camera focus area into several categories. To overcome the challenge of low accuracy we have introduced a novel algorithm for adaptive filtering for the comparison of hue histogram. The results prove that this algorithm is sufficient for accurate image clustering and this may be used in other sports event clustering as well.
Keywords: Event Detection, Cricket, Video Summarization, Image Filtering, Adaptive Filtering.
Scope of the Article: Clustering