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Event detection and summarization in soccer videos using bayesian network and copula
, Article IEEE Transactions on Circuits and Systems for Video Technology ; Volume 24, Issue 2 , February , 2014 , Pages 291-304 ; ISSN: 10518215 ; Karimian, M ; Kasaei, S ; Sharif University of Technology
Abstract
Semantic video analysis and automatic concept extraction play an important role in several applications; including content-based search engines, video indexing, and video summarization. As the Bayesian network is a powerful tool for learning complex patterns, a novel Bayesian network-based method is proposed for automatic event detection and summarization in soccer videos. The proposed method includes efficient algorithms for shot boundary detection, shot view classification, mid-level visual feature extraction, and construction of the related Bayesian network. The method contains of three main stages. In the first stage, the shot boundaries are detected. Using the hidden Markov model, the...
Automatic Highlight Detection in Football Videos using Audio and Video Information
, M.Sc. Thesis Sharif University of Technology ; Manzuri, Mohammad Taghi (Supervisor)
Abstract
Today, with the spread of various videos especially sports video and availability of them, the need for automated methods for search and retrieval of concepts from videos is strongly felt. On the other hand, summarizing video in order to making significant parts of them available is very important. One of the broadest scope that researchers have provided methods for extracting semantic concepts, is soccer videos. Often to extract high-level events, we need a definition and use of intermediate concepts. In this thesis "replay", "audio highlights" and "view type" are used to extract important events in the game. Here, two new methods are introduced for replay detection and view type...
Extraction of Important Events in Football Videos Using Video Summarization Techniques
, M.Sc. Thesis Sharif University of Technology ; Kasaei, Shohreh (Supervisor)
Abstract
Semantic video analysis and automatic concept extraction play an important role in several application including designing content-based search engines, video indexing, and video summarization. Since constructing an appropriate summarized video requires extraction of internal video concepts, video summarization is considered as an application of semantic analysis. The proposed system contains three main stages. In the first stage, the shot boundaries are detected, then using the hidden Markov model (HMM), the video is segmented into larger semantic units, called “play-break” sequences. In the next stage, several features are extracted from each of these units. Finally, in the last stage, in...