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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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Subject: search.filters.subject.HMM

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    Incorporating frequent pattern analysis into multimodal HMM event classification for baseball videos
    (2016-05)
    Chen, Hsuan-Sheng
    ;
    Tsai, Wen-Jiin
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    資訊工程學系
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    Department of Computer Science
    Data mining and frequent pattern analysis have recently become a popular way of discovering new knowledge from a data set. However, it is rarely applied to video semantic analysis. Therefore, this paper introduces two methods: frequent-pattern trained HMM and frequent-pattern tailored HMM to incorporate frequent pattern analysis into multimodal HMM event classification for baseball videos. Besides, different symbol coding methods including temporal sequence coding and co-occurrence symbol coding for multimodal HMM classification are compared. The results of our experiments on baseball video event classification demonstrate that integration of frequent pattern analysis could help to improve event classification performances.
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    設計與開發部落格輔助寫作系統
    (2011)
    李嘉晃
    ;
    LEE CHIA-HOANG
    ;
    國立交通大學資訊工程學系（所）
    由於網路資訊的發達，越來越多的人們習慣於部落格上發表各類文章，分享生活上的點點滴滴，其中使用者的年齡層範圍，不僅涵蓋國中與國小的學生，甚至包括部份的銀髮族。於撰寫部落格的過程中，有時候靈感源源不絕，文章揮灑自如，卻也不乏腸枯思竭的狀況發生。本篇論文結合人機互動與自然語言兩門領域，提出並實作一套部落格文章輔助寫作系統，目的是幫助使用者在撰寫部落格文章的過程中，若發生不知從何構思詞句下筆寫作時，本系統能夠適時適度的提供文章寫作的概念和方向，激發使用者創作的泉源。
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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
    ;
    Tsai, Wen-Jiin
    ;
    資訊工程學系
    ;
    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
    ;
    Lee, Suh-Yin
    ;
    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.