TY - GEN
T1 - Soccer video event detection by fusing middle level visual semantics of an event clip
AU - Qian, Xueming
AU - Liu, Guizhong
AU - Wang, Huan
AU - Li, Zhi
AU - Wang, Zhe
PY - 2010
Y1 - 2010
N2 - Highlight event detection is a fundamental step of semantic based video retrieval and personalized sports video browsing. In this paper, an enhanced hidden Markov models (EHMM) based soccer video event detection method is proposed. Firstly, each soccer video shot is classified into one of the thirteen middle level semantics. Then the sequential soccer video sequence is segmented into event clips. Finally, HMMs are utilized to model the defined four highlights (goal, shoot, foul, and placed kick) and a normal kick. Not only the transitions of the middle level semantics and but also the overall features of an event clip are fused by HMMs to determine the event type. Comparisons are made with some existing soccer video event detection approaches. Experimental results show the effectiveness of the proposed EHMM based soccer video event detection approach. The influences of hidden state number and overall feature types to the event detection performances are discussed.
AB - Highlight event detection is a fundamental step of semantic based video retrieval and personalized sports video browsing. In this paper, an enhanced hidden Markov models (EHMM) based soccer video event detection method is proposed. Firstly, each soccer video shot is classified into one of the thirteen middle level semantics. Then the sequential soccer video sequence is segmented into event clips. Finally, HMMs are utilized to model the defined four highlights (goal, shoot, foul, and placed kick) and a normal kick. Not only the transitions of the middle level semantics and but also the overall features of an event clip are fused by HMMs to determine the event type. Comparisons are made with some existing soccer video event detection approaches. Experimental results show the effectiveness of the proposed EHMM based soccer video event detection approach. The influences of hidden state number and overall feature types to the event detection performances are discussed.
KW - Hidden Markov Models
KW - event detection
KW - soccer video
UR - https://www.scopus.com/pages/publications/78049423526
U2 - 10.1007/978-3-642-15696-0_41
DO - 10.1007/978-3-642-15696-0_41
M3 - 会议稿件
AN - SCOPUS:78049423526
SN - 3642156959
SN - 9783642156953
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 439
EP - 451
BT - Advances in Multimedia Information Processing, PCM 2010 - 11th Pacific Rim Conference on Multimedia, Proceedings
T2 - 11th Pacific Rim Conference on Multimedia, PCM 2010
Y2 - 21 September 2010 through 24 September 2010
ER -