博碩士論文 945202008 詳細資訊




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姓名 陳建昌(Chien-Chang Chen)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 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)
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摘要(中) 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。
摘要(英) 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.
關鍵字(中) ★ 精華擷取
★ 多媒體內容分析
關鍵字(英) ★ video analysis
★ sport highlight extraction
論文目次 摘 要 i
Abstract ii
致 謝 iii
目 錄 iv
圖目錄 vi
表目錄 viii
第一章 緒論 1
1-1 研究動機與目的 1
1-2 運動比賽影片分析方法 3
1-3 論文架構 4
第二章 背景知識 5
2-1 MPEG 視訊壓縮標準簡介 5
2-2 SVM 簡介 10
第三章 相關研究 12
3-1 視訊資料分析 12
3-2文字資訊分析 13
3-3聲音訊號分析 14
3-4 慢動作鏡頭偵測 16
第四章 研究方法 18
4-1 系統概述 18
4-2 串場效果觀察與分析 19
4-3 特徵擷取 22
4-4 場景切換偵測 24
4-5 產生處理片段 27
4-6 建立串場效果樣板 36
4-7 重播片段分析 41
4-8 投手主視角搜尋 46
第五章 實驗結果 48
5-1 串場效果形式 48
5-2 串場效果偵測 52
5-3 精采畫面辨識 55
第六章 結論與未來方向 56
參考文獻 57
參考文獻 [1] D. Tjondronegoro, Y.-P. Phoebe Chen, and B. Pham, “Integrating highlights for more complete sports video summarization,” IEEE Multimedia, vol. 11, no. 4, page 22–37, Oct.–Dec. 2004.
[2] Dian Tjondronegoro, Yi-Ping Phoebe Chen and Binh Pham, “Sports Video Summarization using Highlights and Play-Breaks”, The 5th International ACM Multimedia Information Retrieval Workshop, address Berkeley USA, Nov. 2003.
[3] A. Kokaram, N. Rea, R. Dahyot, M. Tekalp, P. Bouthemy, P. Gros, and I. Sezan, “Browsing sports video”, IEEE Signal Processing Mag., vol. 23, no. 2, page 47–58, 2006.
[4] D. Zhong and S. Chang, “Structure analysis of sports video using domain models,” in Proc. Int. Conf. Multimedia and Expo, Tokyo, Aug. 2001.
[5] Y. Gong, L.T. Sin, C.H. Chuan, H. Zhang, and M. Sakauchi, “Automatic parsing of TV soccer programs,” in Proc. Int. Conf. Multimedia Computing and Systems, May 1995, vol. 7, page 167–174.
[6] P. Chang, M. Han, and Y. Gong, “Extract highlights from baseball game video with hidden Markov models,” in Proc. IEEE Int. Conf. Image Processing, Sept. 2002, page 609–612
[7] Gu Xu, Yu-Fei Ma, Hong-Jiang Zhang and Shi-Qiang Yang, “A HMM based semantic analysis frame work for sports game event detection”, Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on, volume 1, Sept. 2003.
[8] Niall Rea, Rozenn Dahyot and Anil Kokaramn, “Modeling High Level Structure in Sports with Motion Driven HMM,” Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on, volume 3, pages 621-624, May 2004.
[9] Gu Xu, Yu-Fei Ma, Hong-Jiang Zhang and Shi-Qiang Yang, “An HMM-based frame work for video semantic analysis”, Circuits and Systems for Video Technology, IEEE Transactions on, volume 4, pages 1422-1433, Nov. 2005.
[10] Chang, P., Han, M., Gong, Y.: Extract highlights from baseball game video with hidden Markov models. In: Proceedings of the International Conference on Image Processing (ICIP '02)
[11] Hao Jiang, Lie Lu and Hong-Jiang Zhang, “A Robust Audio Classification and Segmentation Method”, International Multimedia Conference; Vol. 9 Proceedings of the ninth ACM international conference on Multimedia, volume 9, pages 203-211, 2001.
[12] Yong Rui, Anoop Gupta and Alex Acero, “Automatically extracting highlights for TV Baseball programs”, International Multimedia Conference archive Proceedings of the eighth ACM international conference on Multimedia, pages 105-115, 2000.
[13] Z. Xiong, R. Radhakrishnan, A. Divakaran, and T.S. Huang, “Audio Events Detection based Highlights Extraction from Baseball, Golf and Soccer Games in A Unified Framework”, ICASSP 2003.
[14] D. Zhang and D. Ellis, "Detecting sound events in basketball video archive," Tech. Rep., Electrical Engineering Department of Columbia university, 2001.
[15] R. Radhakrishan, Z. Xiong, A. Divakaran and Y. Ishikawa , "Generation of sports highlights using a combination of supervised and unsupervised learning in audio domain, " IEEE Pacific-Rim Conference On Multimedia, Singapore, Dec 2003.
[16] Jane C. Boulton, “Two mechanisms for the detection of slow motion”, Journal of the Optical Society of America A: Optics, Image Science, and Vision, volume 4, pages 1634-1642, Aug. 1987.
[17] Vikrant Kobla, Daniel DeMenthon and David Doermann, “Detection Of Slow-Motion Replay Sequences For Identifying Sports Videos”, IEEE Workshop on Multimedia Signal Processing, 1999.
[18] Lifang Gu, Don Bone and Graham Reynolds, “Replay Detection in Sports Video Sequences”, CSIRO Mathematical and Information Sciences.
[19] Jinjun Wang, Engsiong Chng and Changsheng Xu, “Soccer replay detection using scene transition structure analysis”, volume: 2, pages: ii/433- ii/436, Mar. 2005
[20] H. Pan, P. Van Beek and M. I. Sezan, “Detection of Slow-motion Replay Segments in Sports Video for Highlights Generation”, IEEE International Conference on Acoustic, Speech and Signal Processing, 2001.
[21] Lei Wang, Xu Liu, S. Lin, Guang-You Xu and Heung-Yeung Shum, “Generic slow-motion replay detection in sports video”, Image Processing, 2004. ICIP '04. 2004 International Conference on, volume 3, pages 1585-1588, Oct. 2004.
[22] E. J. Farn, L. H. Chen and J.H. Liou, “A new slow-motion replay extractor for soccer game videos”, International Journal of Pattern Recognition and Artificial Intelligence, volume 17, pages 1467-1481, 2003.
[23] “Automatic Soccer Video Analysis and Summarization”, IEEE Transactions on Image Processing, Volume 12, Issue 7, page 796 – 807, July 2003.
[24] Ling-Yu Duan , Min Xu , Xiao-Dong Yu , Qi Tian, “A unified framework for semantic shot classification in sports videos”, Proceedings of the tenth ACM international conference on Multimedia, December 01-06, 2002, Juan-les-Pins, France.
[25] H. Denman, N. Rea, and A. Kokaram, “Content-based analysis for video from snooker broadcasts,” J. Computer Vision Image Understand., Special Issue on Video Retrieval and Summarization, vol. 92, pp. 141–306, Nov./Dec. 2003.
[26] R. Dahyot, N. Rea, and A. Kokaram, “Sport video shot segmentation and classification,” in Proc. PIE Int. Conf. Visual Communication and Image Processing, July 2003, page 404–413.
[27] E. Kijak, G. Gravier, P. Gros, L. Oisel, and F. Bimbot, “HMM based structuring of tennis videos using visual and audio cues,” in Proc. IEEE Int. Conf. Multimedia and Expo, July 2003, vol. 3, page 309–312.
[28] A. Ekin, A.M. Tekalp, and R. Mehrotra, “Automatic soccer video analysis and summarization,” IEEE Trans. Image Processing, vol. 12, no. 7, page 796–807, July 2003.
[29] R. Dahyot, N. Rea, A. Kokaram, and N. Kingsbury, “Inlier modeling for multimedia data analysis,” in Proc. IEEE Int. Workshop Multimedia Signal Processing, Sep. 29–Oct. 1 2004, page 482–485.
[30] G. Millerson, The Technique of Television Production, 12th ed. New York: Focal, March 1990.
[31] A. M. Ferman and A. M. Tekalp, “A fuzzy framework for unsupervised video content characterization and shot classification,” J. Electron. Image, vol. 10, no. 4, pp. 917–929, Oct. 2001.
[32] ISO/IEC, MPEG Standard, http://www.mpeg.org,1998.
[33] ISO/IEC International Standard 13818-2-2:1995.
[34] ISO/IEC International Standard 14496-2:2001.
[35] Vapnik, V. , "Statistical Learning Theory," New York, NY: Wiley, 1998
[36] Chang, C. et al, "The analysis of decomposition methods for support vector machines," IEEE Transations on Neural Networks, 2000 , 11 (4): 1003 ~1008
[37] C.J.C. Burges. “A tutorial on support vector machines for pattern recogition.” Data Mining and Knowledge Discovery, 2(2)︰955-974,1998.
[38] N.Cristianini, J. Shawf-Taylor. “An Introduction to Support Vector Machines and other kernel-based learning methods,” Cambridge University Press,2000.
[39] Steve R. Gunn. “Support Vector Machines for Classification and Regression,” University of Southampton, Technical Report 1998.
[40] Yu Zhong, Hongjiang Zhang, and Anil K. Jain, “Automatic Caption Localization in Compressed Video,” IEEE Transaction on Pattern Analysrs and Machine Intelligence, vol. 22, no. 4, page 385–392, April 2000.
[41] D. Zhang, R.K. Rajendran, S.F. Chang, “General and domain-specific techniques for detecting and recognizing superimposed text in video,” IEEE 2002 International Conference on image processing, September 22-25, 2002.
[42] Zhang, D., Chang, S.F., “Event Detection in Baseball Video using Superimposed Caption Recognition,” Proc. ACM Multimedia 2002, Juan Les Pins, France, December 2002.
指導教授 蘇柏齊(Po-Chyi Su) 審核日期 2007-7-23
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