• Dharmesh R. Tank
• Dr Devang S. Pandya

Traditionally video were analyzed manually, however this costs valuable time. To sustain increasing growth of video data, there is an emerging demand. Therefore it is necessary to have an approach to make the video analysis task faster and automatically. Automatic video summarization is about extracting important events from original video to produce general summaries for the most important moments by interest. One way for creating a video summary is by extracting the features and then selecting key frames from these segment. Even though this approach is used for automatic video summarization, user cannot retrieve video intuitively, based on high level concepts. To solve this type of problem, event detection based video summarization is proposed in this paper. Proposed event detection approach aims to extract high level events like goal, player exchange and other types using Bayesian network.

Video Summarization, Key Frame, Video Skimming, Event Detection, Bayesian Network.

"EVENT DETECTION IN SOCCER VIDEO USING BAYESIAN NETOWK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.1709-1725, July-2018, Available :http://www.jetir.org/papers/JETIRC006297.pdf

"EVENT DETECTION IN SOCCER VIDEO USING BAYESIAN NETOWK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp1709-1725, July-2018, Available at : http://www.jetir.org/papers/JETIRC006297.pdf