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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/9362

    Title: 植基於串場效果偵測與內容分析之棒球比賽精華擷取系統;A Baseball Highlight Extraction Scheme based on Transition Effect Detection and Content Analysis
    Authors: 陳建昌;Chien-Chang Chen
    Contributors: 資訊工程研究所
    Keywords: 精華擷取;多媒體內容分析;video analysis;sport highlight extraction
    Date: 2007-07-11
    Issue Date: 2009-09-22 11:46:11 (UTC+8)
    Publisher: 國立中央大學圖書館
    Abstract: 由於數位化與儲存技術的進步,多媒體資訊在應用的需求上不斷成長,對於數位視訊資料提供快速搜尋機制,甚至取出精華等成為當今研究的重點。而運動比賽分析是視訊研究的主要項目之ㄧ,其在娛樂與商業上的價值相當高,考慮一般比賽時間較長且精華片段較一般影片明確,本論文提出一種快速且準確的運動比賽精華萃取系統,以提供使用者更佳的服務,並以棒球比賽為主要測試項目。 轉播單位較觀眾具有專業水準,因此當出現精采畫面時,會提供相關重播鏡頭給觀眾欣賞。為了區隔重播片段與現場畫面,因此會利用串場效果作為緩衝。由於各家轉播單位與轉播的內容往往大相逕庭,串場效果也是呈現多樣化。本研究藉由通用性的串場效果偵測,找出串場效果,並由此定位重播片段位置,進而分析重播片段內容,找出球賽精華。最後再由重播片段往前搜尋,找到原始事件位置,作為精華片段的標記位置。整個系統建構在現今使用的數位儲存格式MPEG視訊壓縮的資訊做計算,節省大量複雜運算。實驗結果也顯示本系統具有相當高的準確度與效率。 Watching sports videos has always been an important and popular recreation. The audiences nowadays can enjoy watching the sports games at home with their high-quality audio-visual facilities and even record the videos by using digital video recorders. When the audiences choose to record the video for time-shift purposes, they may not be interested in watching the whole game but the video highlights only. In addition, the highlight parts in current sportscasts are always followed by slow-motion replays. A transition effect is usually inserted between the normal frame and the replaying frame to inform the audiences of the replay. Therefore, the appearance of a transition effect has a direct linkage to the video highlight. In this research, we propose to detect transition effects for baseball videos highlight extraction. In order to reduce the computational cost of hardware, the proposed method processes MPEG compressed bit-streams directly. We make use of the color information of MPEG streams and the motion information including motion vectors and the macro-block types in frames. Then we analyze to determine whether the transition effects occur by the characteristics of transition effects. Next, we use the detected transition effects to train a template, which will be used for matching in the remaining parts of video. Furthermore, we classify the replay segments so that the user can choose the video segment that he or she really likes to watch. Since the users will be more interested in watching the normal scenes of highlights, we trace back to find out the pitching view as the starting point of a highlight. Experimental results show the feasibility of the highlight extraction system.
    Appears in Collections:[資訊工程研究所] 博碩士論文

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