棒球影片場景剖析與分類方法

本論文提出了一套棒球視訊場景分類系統。採用影像內容分析方式，自動剖析棒球比賽影片，以取得棒球比賽影片中的重要畫面。首先利用球場及球衣的顏色比例偵測，配合場景變動偵測，挑選出影片中數段候選重要場景。再利用影像上的特徵分析各重要場景畫面，如：物體變動偵測、球場與球衣顏色分佈、攝影機運動參數估計、關鍵畫面分析，及變動位置圖(Motion Map)比對等。最後根據上述特徵，利用事先規劃好的規則來做場景分類判斷，以便最後能把符合重要場景條件的結果，以時間碼(Time Code)配合場景類別的方式，在後續的影片資料庫裡建立索引。

關鍵字

影像內容分析；場景變動偵測；變動位置圖；攝影機參數估測；場景分類

並列摘要

The thesis proposes a scene parsing and classification system for baseball videos. The system automatically parses baseball video and extracts import scenes with image content analysis. Firstly, the system selects several candidate import scenes by field/cloth color ratio and scene change detection. Secondly, the system utilizes image features, e.g. object motion detection, field and cloth color detection, camera motion parameters, key-frame analysis, and motion-map comparison, etc, to analysis each candidate import scenes. Finally, the system classifies scenes according to above-mentioned features and predefined rules. Subsequently, the system will establish indexes of scenes correspond to the rules in baseball video database.

並列關鍵字

Image Content Analysis ； Scene Change Detection ； Motion Map ； Camera Motion Parameter Estimation ； Scene Classification

參考文獻

[19]. 張厥煒、譚哲杰，「桌球場中視訊物件分割與追蹤方法」，國立台北科技大學資訊工程系研究所碩士論文，民國94年。

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[5]. C. L. Huang; C. Y. Chang, "Video Summarization Using Hidden Markov Model," Proc. of IEEE Int'l Conf. on Information Technology: Coding and Computing, pp.473-477, 2001.

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棒球影片場景剖析與分類方法

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