Learning and inferencing in user ontology for personalized Semantic Web search
Information Sciences: an International Journal
Foundations and Trends in Information Retrieval
Discovering event evolution graphs from news corpora
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A review of vision-based systems for soccer video analysis
Pattern Recognition
Using scripts for affective content retrieval
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Soccer video event detection by fusing middle level visual semantics of an event clip
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Automatic video genre categorization and event detection techniques on large-scale sports data
Proceedings of the 2010 Conference of the Center for Advanced Studies on Collaborative Research
EURASIP Journal on Advances in Signal Processing
An event-based video retrieval system by combining broadcasting baseball video and web-casting text
Proceedings of the 2011 ACM Symposium on Applied Computing
Automatic player detection, tracking and mapping to field model for broadcast soccer videos
Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia
Summarizing sporting events using twitter
Proceedings of the 2012 ACM international conference on Intelligent User Interfaces
A Generic Approach for Systematic Analysis of Sports Videos
ACM Transactions on Intelligent Systems and Technology (TIST)
HMM based soccer video event detection using enhanced mid-level semantic
Multimedia Tools and Applications
Expert Systems with Applications: An International Journal
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Assessing team strategy using spatiotemporal data
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Exploiting content relevance and social relevance for personalized ad recommendation on internet TV
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Features extraction for soccer video semantic analysis: current achievements and remaining issues
Artificial Intelligence Review
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Sports video semantic event detection is essential for sports video summarization and retrieval. Extensive research efforts have been devoted to this area in recent years. However, the existing sports video event detection approaches heavily rely on either video content itself, which face the difficulty of high-level semantic information extraction from video content using computer vision and image processing techniques, or manually generated video ontology, which is domain specific and difficult to be automatically aligned with the video content. In this paper, we present a novel approach for sports video semantic event detection based on analysis and alignment of Webcast text and broadcast video. Webcast text is a text broadcast channel for sports game which is co-produced with the broadcast video and is easily obtained from the Web. We first analyze Webcast text to cluster and detect text events in an unsupervised way using probabilistic latent semantic analysis (pLSA). Based on the detected text event and video structure analysis, we employ a conditional random field model (CRFM) to align text event and video event by detecting event moment and event boundary in the video. Incorporation of Webcast text into sports video analysis significantly facilitates sports video semantic event detection. We conducted experiments on 33 hours of soccer and basketball games for Webcast analysis, broadcast video analysis and text/video semantic alignment. The results are encouraging and compared with the manually labeled ground truth.