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Access type: Open accessSubject: search.filters.subject.HMM

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    A framework for video event classification by modeling temporal context of multimodal features using HMM
    (2014-02-01)
    Chen, Hsuan-Sheng
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    Tsai, Wen-Jiin
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    資訊工程學系
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    Department of Computer Science
    Semantic high-level event recognition of videos is one of most interesting issues for multimedia searching and indexing. Since low-level features are semantically distinct from high-level events, a hierarchical video analysis framework is needed, i.e., using mid-level features to provide clear linkages between low-level audio-visual features and high-level semantics. Therefore, this paper presents a framework for video event classification using temporal context of mid-level interval-based multimodal features. In the framework, a co-occurrence symbol transformation method is proposed to explore full temporal relations among multiple modalities in probabilistic HMM event classification. The results of our experiments on baseball video event classification demonstrate the superiority of the proposed approach. (C) 2013 Elsevier Inc. All rights reserved.
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    HMM-based ball hitting event exploration system for broadcast baseball video
    (2012-07-01)
    Chen, Hua-Tsung
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    Chou, Chien-Li
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    Tsai, Wei-Chin
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    Lee, Suh-Yin
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    Lin, Bao-Shuh P.
    With the dramatic growth of fandom population, a considerable amount of research efforts have been devoted to baseball video processing. However, little work focuses on the detailed follow-ups of ball hitting events. This paper proposes a HMM-based ball hitting event exploration system for broadcast baseball video. Utilizing the strictly-defined layout of the baseball field, the proposed system first detects the game-specific spatial patterns in the field, such as the field lines, the bases, the pitch mound, etc. Then, the play region the currently camera-focused region of the baseball field is identified for frame type classification. Since the temporal patterns of presenting the game progress follow a prototypical order, we consider the classified frame types as observation symbols and recognize ball hitting events using HMM. Experiments conducted on broadcast baseball video show encouraging results in frame type classification and ball hitting event recognition. Three practical applications, including highlight clip extraction by user-designated query, storyboard construction, and similar event retrieval, are introduced to address the applicability of our system. (C) 2012 Elsevier Inc. All rights reserved.