博碩士論文 955202082 詳細資訊




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姓名 藍啟恆(Chi-Heng Lan)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 棒球比賽精華片段擷取分類系統
(A Highlight Extraction and Classification Scheme for Baseball Video)
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摘要(中) 本論文提出一個實用的棒球比賽精華片段擷取與分類的方法。由於棒球比賽時間較久,若使用者需要在短時間內瀏覽多場比賽,一個自動的精華片段擷取將帶來許多便利。值得注意的是,精華片段擷取可視為一個數位錄影機的附屬功能,因此,它所耗費的計算資源應該遠少於數位視訊的解壓縮過程以符合實際應用的需求。我們所提出的系統首先將偵測所謂串場效果的位置。由於棒球比賽精彩片段重播出現的前後,通常會由電視台加入串場效果以告知觀眾,我們利用串場效果獨特的視覺特性,準確偵測其位置,即重播畫面出現處。接著,我們以SVM (Support Vector Machine)分類器找出投打對決畫面,作為此段重播實際畫面的起點。再來,我們對於這些精彩畫面以HMM (Hidden Markov Model)加以分析與分類,將內外野精采畫面的情境擷取出來,讓使用者更容易得到所需的內容。本系統主要是建構在MPEG2數位視訊壓縮格式上,即我們有效利用壓縮後的MPEG串流資訊,做為後續分析與處理的主要參考依據。如此設計不僅有效降低系統運算的複雜度,也讓我們的系統與其它已提出的方法相較,更具有實用性。實驗結果顯示,我們所提出的系統具有相當高的準確度。
摘要(英) This paper presents a practical highlight extraction and classification schemes for baseball videos. The approach relies on precise detections of transition effects inserted at the beginning and the end of the replays in the game, which demonstrate the game highlights. It is worth noting that the complexity of the highlight extraction procedure should be limited since it is an auxiliary function of a digital video recorder. Therefore, in the proposed system, the features of MPEG compressed videos are used for subsequent processing to archive efficiency. The properties of transition effects are exploited so that the effects can be accurately retrieved for locating the video segments of replays. Next, the pitching view, which is the starting point of every play in baseball games, will be extracted via Support Vector Machine (SVM). The contents of the play can then be analyzed and classified to determine their types or exciting levels. We classify the extracted highlight segments by using Hidden Markov model (HMM). Experimental results show that the accuracy is good enough to achieve the practical highlight extraction for baseball videos.
關鍵字(中) ★ 棒球
★ 精華擷取
★ 片段分類
★ 支持向量機
★ 隱藏式馬可夫模型
關鍵字(英) ★ HMM
★ SVM
★ highlight classification
★ highlight extration
★ baseball
論文目次 摘 要 i
Abstract ii
致謝詞 iii
圖目錄 viii
表目錄 x
第一章 簡介 1
1-1 研究動機與目的 1
1-2 影片內容分析方法 2
1-3 論文架構 4
第二章 相關研究 5
2-1 精彩片段擷取 5
2-1-1 視覺特徵 5
2-1-2 文字分析 7
2-1-3 慢動作重播 8
2-1-4 聲音特徵 10
2-1-5 混合特徵 11
2-2 內容語意分析 12
2-2-1 條件方式(rule-base) 12
2-2-2 機率方式(probabilistic method) 13
第三章 背景知識 15
3-1 MPEG 視訊壓縮格式簡介 15
3-2 SVM (Support Vector Machine) 介紹 20
3-3 HMM (Hidden Markov Model) 介紹 21
第四章 精彩片段擷取與分類 28
4-1 系統概述 28
4-2 串場效果偵測 30
4-2-1 特徵擷取 30
4-2-2 場景轉換偵測 32
4-2-3 產生處理片段單元 35
4-2-4 串場效果分析與建立樣板 37
4-3 投手主視角畫面搜尋 43
4-4 精彩片段分類 46
4-4-1 精彩片段分析 46
4-4-2 精彩片段鏡頭分類 48
4-4-3 精彩片段分類 52
第五章 實驗結果 55
5-1 場景轉換偵測 55
5-2 串場效果偵測 56
5-3 精彩片段分類 58
第六章 討論與未來方向 60
參考文獻 61
附件一、棒球守備位置說明 69
參考文獻 [1] V. Tovinkere and R. J. Qian, “Detecting semantic events in soccer games: toward a complete solution,” Proc. IEEE International Conference on Multimedia & Expo. 2001.
[2] A. Hanjalic, “Adaptive extraction of highlights from a sport video based on excitement modeling,” Proc. IEEE Transactions on Multimedia, vol. 7, no. 6, Dec. 2005.
[3] J. Assfalg, M. Bertini, C. Colombo, A. del Bimbo, and W. Nunziati, “Semantic annotation of soccer videos: Automatic highlights identification,” Proc. Computer Vision and Image Understanding, vol. 92, no. 2-3, Nov. 2003.
[4] D. Tjondronegoro, Y. –P. Chen, and B. Pham, “Integrating highlights for more complete sports video summarization,” Proc. IEEE Multimedia, vol. 11, no. 4, Oct.-Dec. 2004.
[5] J. Assfalg, M. Bertini, A. D. Bimbo, W. Nunziati and P. Pala, “Soccer highlights detection and recognition using HMMs,” Proc. IEEE International Conference on Multimedia and Expo., Lausanne, Aug. 2002.
[6] M. Petkovic, V. Mihajlovic, W. Jonker and S. Djordjevic-Kajan, “Multi-modal extraction of highlights from tv formula 1 Programs,” Proc. IEEE International Conference on Multimedia and Expo., Lausanne, Aug. 2002.
[7] C.-C. Cheng and C.-T. Hsu, “Fusion of audio and motion information on HMM-based highlight extraction for baseball games,” Proc. IEEE Transactions on Multimedia, vol. 8, no. 3, Jun. 2006.
[8] T. Mochizuki, M. Tadenuma and N. Yagi, “Baseball video indexing using patternization of scenes and hidden Markov model,” Proc. IEEE International Conference on Image Processing, 2005.
[9] P. Chang, M. Han, and Y. Gong, “Extract highlights from baseball game video with hidden Markov models,” Proc. IEEE International Conference on Image Processing, 2002.
[10] L. Rabiner, “A tutorial on hidden Markov models and selected applications in speech recognition,” Proc. IEEE, vol. 77, no. 2, Feb. 1999.
[11] D. Tjondornrgoro, Y.-P. Phoebe. Chen, and B. Pham, “Sports video summarization using highlights and play-breaks,” Proc. The 5th International ACM Multimedia Information Retrieval Workshop, address Berkeley USA, Nov. 2003.
[12] A. Kokaram, N. Rea, R. Dahyot, M. Tekalp, P. Bouthemy, P. Gros and I. Sezan, “Browsing sports video: Trends in sports-related indexing and retrieval work,” Proc. IEEE signal Processing Mag., vol. 23, no. 2, page 47-58, 2006.
[13] D. Zhong and S.F. Chang, “Structure analysis of sports video using domain models,” Proc. IEEE International Conference on Multimedia and Expo. ’01, 2001.
[14] A. Ekin, A. Muart Tekalp and R. Mehrotra, “Automatic soccer video analysis and summarization,”Proc. IEEE Transaction on Image Processing, vol. 12, no. 7,page 796-807,  Jul. 2003.
[15] Y. Gong, L.T. Sin, C.H. Chuan, H. Zhang and M. Sakauchi, “Automatic parsing of TV soccer programs,” Proc. IEEE International Conference on Multimedia Computing and Systems, vol. 7, page 167-174, May 1995.
[16] L.-Y. Duan, M. Xu, X.-D. Yu and Q. Tian, “A unified framework for semantic shot classification in sports videos,” Proc. IEEE Transaction on Multimedia, vol. 7, no. 6, page 1066-1083, Dec. 2005.
[17] Y.P. Tan, D.D. Saur, S.R. Kulkarni and P.J. Ramadge, “Rapid Estimation of camera motion from compressed video with application to video annotation,” Proc. IEEE Transaction on Circuits and Video Technology, vol. 10, no. 1, Feb. 2000.
[18] A. Bonzanini, R. Leonardi and P. Migliorati, “Event recognition in sport programs using Low-Level motion indices,” Proc. IEEE International Conference on Multimedia and Expo, 2001.
[19] D. Zang, and S.F. Chang, “Event detecting in baseball video using superimposed caption recognition,” Proc. ACM Multimedia 2002, Juan Les Paris, France, Dec. 2002.
[20] D. Zang, R.K. Rajendran, and S.F. Chang, “General and domain-specific techniques for detecting and recognizing superimposed text in video,” Proc. IEEE International Conference on Image Processing, Sep. 2002.
[21] J.C. Boulton, “Two mechanisms for detection of slow motion,” Proc. Journal of the Optical Society of America A: Optics, Image Science, and Vision, vol. 4, page1634-1642, Aug. 1987.
[22] V. Kobla, D. DeMoenthon and D. Doermann, “Detection of slow-motion replay sequences for identifying sports videos,” Proc. IEEE Workshop on Multimedia Signal Processing, 1999.
[23] L. Gu, D. Bone and G. Reynolds, “Replay detection in sports video sequences,” Proc. the Eurographics Workshop on Multimedia, Multimedia'99, Eds. Correia N., Chambel T. and Davenport D., Springer Verlag, pp. 3-12, Milan, Italy, Sep. 1999.
[24] J. Wang, E. Chng and C. Xu, “Soccer Replay Detection using Scene Transition Structure Analysis,” Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'2005), vol. 2, pp. 433-436 Pennsylvania, USA, Mar. 2005.
[25] H. Pan, P. Van Beek and M.I. Sezan, “Detection of slow-motion replay segments in sports video for highlights generation,” Proc. IEEE International Conference on Acoustic, Speech and Signal Processing, vol. 3, pp. 1649-1652, 2001.
[26] L. Wang, X. Liu, S. Lin, G.-Y. Xu and H.-Y. Shum, “Generic slow-motion replay detection in sports video,” Proc. IEEE International Conference on Image Processing, vol. 3, pp. 1585-1588, Oct. 2004.
[27] E.J. Farn, L.H. Chen and J.H. Liou, “A new slow-motion replay extractor for soccer game videos,” Proc. International Journal of Pattern Recognition and Artificial Intelligence, vol. 17, pp. 1467-1481, 2003.
[28] H. Jiang, L. Lu, and H.J. Zhang, “A robust audio classification and segmentation method,” Proc. ACM International Conference on Multimedia, Ottawa, Ontario, Canada, vol. 9, pp.203-211, Sep. 2001.
[29] Y. Rui, A. Gupta and A. Acero, “Automatically extracting highlights for TV baseball programs,” Eighth ACM International Conference on Multimedia, pp.105-115, 2000.
[30] Z. Xiong, R. Radhakrishnan, A. Divakaran and T. Huang, “Audio events detection based highlights extraction from baseball, golf and soccer games in a unified framework,” Proc. IEEE International Conference on Acoustic, Speech and Signal Processing 2003, Apr. 2003.
[31] R. Leonardi, P. Migliorati and M. Prandini, “Sematic indexing of sports program sequences by Audio-Visual analysis,” Proc. IEEE International Conference on Image Processing, Sep. 2003.
[32] Y.-L. Chang, W. Zeng, I. Kamel and R. Alonso, “Integrated image and speech analysis for content-based video indexing,” Proc. IEEE International Conference on Multimedia Computing and Systems, 1996.
[33] S.-C. Chen, M.-L. Shyu, W. Liao and C. Zhang, “Scene change detection by audio and video clues,” Proc. IEEE International Conference on Multimedia and Expo, 2002.
[34] A. Albiol, L. Torres and J. Delp, “The indexing of persons in news sequences using audio-visual data,” Proc. IEEE International Conference on Acoustic, Speech and Signal Processing, 2003.
[35] W. Hua, M. Han and Y. Gong, “Baseball scene classification using multimedia features,” Proc. IEEE International Conference on Multimedia and Expo, 2002.
[36] A. Hanjalic, “Generic approach to highlight extraction from a sport video,” Proc. IEEE International Conference on Image Processing, Sep. 2003.
[37] Z. Xong, R.Radhakrishnan and A. Divakaran, “Generation of sports highlights using motion activity in combination with a common audio feature extraction framework,” Proc. IEEE International Conference on Image Processing, Sep. 2003.
[38] M. Petkovic, V. Mihajlovic and W. Jonker, “Techniques for automatic video content derivation,” Proc. IEEE International Conference on Image Processing, Sep. 2003.
[39] R. Dahyot, A. Kokaram, N. Rea and H. Denman, “Joint audio visual retrieval for tennis broadcasts,” Proc. IEEE International Conference on Acoustic, Speech and Signal Processing, 2003.
[40] Y. Gong, X. Liu and W. Hua, “Creating motion video summaries with partial audio-visual alignment,” Proc. IEEE International Conference on Multimedia and Expo, 2002.
[41] H.-T. Chen, M.-H. Hsiao, H.-S. Chen, W.-J. Tsai and S.-Y Lee, “A baseball exploration system using spatial pattern recognition,” Proc. IEEE International Symposium on Circuits and Systems, May 2008.
[42] M. Fleischman, B. Roy and D. Roy, “Temporal feature induction for baseball highlight classification,” Proc. ACM Multimedia Conference, Augsburg, Germany, 2007.
[43] B. Moghaddam and A. Pentland, “Probabilistic visual learning for object recognition,” Proc. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no.7, pp. 696-710, Juillet 1997.
[44] L. Xie, S.-F. Chang, A. Divakaran and H. Sun, “Structure analysis of sports video with hidden Markov models,” Proc. IEEE International Conference on Acoustic, Speech and Signal Processing, 2002.
[45] P. Chang, M. Han and Y. Gong, “Extract highlights from baseball game video with hidden Markov models,” Proc. IEEE International Conference on Image Processing, 2002.
[46] G. Xu, Y.-F. Ma, H.-J. Zhang and S.-Q. Yang, “Motion-based event recognition using HMM,” Proc. IEEE International Conference on Pattern Recognition, 2002.
[47] G. Xu, Y.-F. Ma, H.-J. Zhang and S.-Q. Yang, “A HMM based semantic analysis framework for sports game event detection,” Proc. IEEE International Conference on Image Processing, 2003.
[48] G. Xu, Y.-F. Ma, H.-J Zhang and S.-Q. Yang, “An HMM based framework for video semantic analysis,” Proc. IEEE Transactions on Circuits and Systems for Video Technology, vol. 15, no. 11, Nov. 2005.
[49] J. Assfalg, M. Bertini, A. Del Bimbo, W. Nunziati and O. Pala, “Detection and recognition of football highlights using HMM,” Proc. IEEE International Conference on Electronics, Circuits, and Systems, 2002.
[50] N. Rea, R. Dahyot, and A. Kokaramn, “Modeling high level structure in sports with motion driven HMM,” Proc. IEEE International Conference on Acoustic, Speech and Signal Processing, vol. 3, pp. 621-624, May 2004.
[51] G. Jin, L. Tao and G. Xu, “Hidden Markov model based events detection in soccer video,” Proc. International Conference on Image Analysis and Recognition, 2004.
指導教授 蘇柏齊(Po-Chyi Su) 審核日期 2009-2-3
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