博碩士論文 87325032 詳細資訊




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姓名 陳錫勳(Hsi-Husn Chen)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 利用色彩統計與鏡頭運鏡方式作視訊索引
(Video Indexing Using Color Histogram and Camera Operation)
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摘要(中) 視訊索引技術在視訊隨選系統與視訊圖書館系統中扮演相當重要的角色,但是龐大的視訊資料卻是造成瀏覽困難與搜尋不易的最主要原因。完整的視訊索引技術可提供的視訊影片索引方法及影片前處理,使得使用者可以快速搜尋與瀏覽影片。
視訊分段為製作視訊索引的第一個步驟,它可以將影片依鏡頭分割成數個視訊片段。我們使用色彩統計的方法來偵測場景變換與分割影片,其中我們使用了四種不同的色彩空間,共十六種色彩量化的方式來檢驗連續鏡頭中色彩統計的差異值。
當視訊分段完成之後,第二個步驟為關鍵畫面的萃取。關鍵畫面代表著此一視訊片段以供使用者查詢。然而,人們對於關鍵畫面的選擇是以劇情上的代表性為選取標準,所以我們提出使用鏡頭運鏡方式與視訊片段邊界為選擇關鍵畫面的標準;鏡頭運鏡的三個主要的動作分別為:panning、zooming、tilting。將每一個視訊片段偵測出其主要的動作,再依其動作決定關鍵畫面的選擇方式。我們使用光流場來決定鏡頭運鏡的方式,而以Lucas的方法來計算畫面中的光流場分佈。
摘要(英) Video Indexing plays an important role in video libraries and video on demand systems. However, the task of browsing or querying a huge amount of video data is difficult. They require that the source material should be first effectively indexed.
The first step of video indexing is video segmentation, which partitions a video into individual camera shots. In this thesis, we use the histogram-based algorithm to test the difference metrics between adjacent frames and present scene change detection algorithm. Sixteen methods of color quantization for scene change detection are considered in 4 types of color spaces: RGB, HSI, HSV and YIQ. We also compare the performances of different color spaces and their color quantizations on two types of video sequence: film and education video.
The second step is key frame extraction. In a shot, a key frame is selected to represent the shot. The key frame depends heavily on the perception of people. In our work, we combine the shot boundary approach and camera operation models to establish our key frame selection rules. The key frames are selected according to the camera operation models: panning-like, tilting-like and zooming-like sequences. Lucas and Kanade’s method is adopted for estimating optical flow in this step.
Experimental results demonstrate the feasibility and effectiveness of our proposed video indexing system.
關鍵字(中) ★ 視訊分段
★ 鏡頭運鏡
★ 光流場
★ 關鍵畫面
★ 換鏡偵測
★ 色彩量化
★ 色彩統計
關鍵字(英) ★ optical flow
★ key frame
★ scene change detection
★ color quantization
★ color histogram
★ camera operation
★ video segmentation
論文目次 Chapter 1 Introduction
1.1 Motivation
1.2 Survey of related works
1.3 System overview
1.4 Thesis organization
Chapter 2 Video Segmentation
2.1 Effects of scene change
2.2 Color histogram
2.2.1 Color models
2.2.2 Color space quantization
2.2.3 Metrics for scene change
2.3 Algorithm tests
Chapter 3 Key Frame Extraction
3.1 Key Frames
Shot boundary based approach
Visual content based approach
Clustering based approach
Shot activity based approach
3.2 Optical flow
3.2.1 Optical flow theory
3.2.2 Lucas and Kanade’s method
3.3 Camera operation model
3.3.1 Camera operation
3.3.2 Relationship between camera operation and motion vector
3.4 key frame selection rules
Chapter 4 Experimental Results
4.1 Environment
4.2 Experimental result of color quantization
4.2.1 test 1
4.2.2 test 2
4.3 Experimental result of scene change detection
4.4 Experimental result of key frame extraction
Chapter 5 Conclusions and Future Works
5.1 Conclusions
5.2 Future Works
參考文獻 [1] G. Lupatini, C. Saraceno, R. Leonardi, “Scene break detection: a comparison” proceeding 1998 Continuous-Media Database and Application, pp. 34-41 1998
[2] Haitao Jiang, Abdelsalam Helal, Ahmed K. Elmagarmid, Anupam Joshi, “Scene change detection techniques for video database systems” Multimedia System 1998
[3] J. M. Corridoni, A Del Bimbo, “Structured representation and automatic indexing of movie information content” Pattern Recognition, Vol. 31, No 12, pp. 2027-2045, 1998
[4] Akihito Akutsu, Yashinobu Tonomura, Hideo Hashimoto, Yuji Ohba, “Video indexing using motion vectors”, SPIE Vol.1818 Visual Communications and Image Processing, pp. 1522-1530, 1992
[5] Hong Jiang Zhang, Jianhua Wu, Di Zhong, Stephen W. Smoliar, “An Integrated system for conten-Based video retrieval and browsing” Pattern recognition, Vol.30, No. 4, pp. 643-658,1997
[6] Hong Jiang Zhang, Atreyi Kankanhalli, Stephen W. Smoliar, “Automatic partitioning of full-motion video” Multimedia System, Vol.1 pp.10-28, 1993
[7] Edoardo Ardizzone, Marco La Cascia, Davide Molinelli, “Motion and Color-Based video Indexing and Retrieval”, 1996 IEEE proceeding of ICPR, pp. 135-139
[8] Keesook J. Han, Ahmed H. Tewfik, “Eigen-Image Based Video Segmentation and index”, Image processing, 1997, Proceeding of international conference on published 1997, Vol. 4, pp. 538-541
[9] Jonathan D. Courtney, “Automatic video indexing via object motion analysis”, Pattern Recognition, Vol. 30, No. 4, pp. 607-625, 1997
[10] John M. Gauch, Susan Gauch, Sylvain Bouix, Xiaolan Zhu, “Real time video scene detection and classification”, Information Processing and Management 35 (1995) pp. 401-420
[11] Anil Jain, Aditya Vailaya, Wei Xiong, “Query by video clip”, Pattern recognition, 1998 proceedings, 14th Internationsl conference on Published, Vol. 1, pp. 909-911
[12] Michael Irani, P. Anandan, Jim Bergen, Rakesh Kumar, Steve Hsu, “Efficient representations of video sequences and their applications”, Signal Processing: Image Communication Vol. 8, issue 4, pp. 327-351 May 1996
[13] Nilesh V. Patel, Ishwar K. Sethi, “video shot detection and characterization for video databases”, Pattern Recognition, Vol. 30, No. 4, pp. 583-592, 1997
[14] Zabih, R.; Miller, J.; Mai, K.” Video browsing using edges and motion” Computer Vision and Pattern Recognition, 1996. Proceedings CVPR '96, 1996 IEEE Computer Society Conference on , 1996 , Page(s): 439 —446
[15] Pass, G.; Zabih, R. “Histogram refinement for content-based image retrieval“, Applications of Computer Vision, 1996. WACV '96., Proceedings 3rd IEEE Workshop on , 1996 , Page(s): 96 —102
[16] Herzog, A. Miene, TH. Hermes, P. Alshuth “Integrated information mining for tex, images, and video”, Comput. & Graphics, Vol. 22, No. 6, pp. 675-685, 1998
[17] J. L. Barron, D. J. Fleet, and S. S. Beauchemin. “Performance of optical flow techniques”. International journal of computer vision, 12(1) pp. 23-77, 1994
[18] Rafael C. Gonzalez, and Richard E. Woods “Digital Image Processing” 2nd ed., Addison-Wesley Publishing Company, 1993, pp. 225-236
[19] H. Palus and D. Bereska “The Comparison between transformations from RGB color space to HIS color space, used for object recognition” image processing and its applications 4-6 July 1995 conference publication No. 410
[20] John R. Smith and Shih-Fu Chang “Tool and techniques for color image retrieval”, IS&T/ SPIE proceedings vol. 2670, storage & retrieval for image and video databases IV
[21] Ralph M. Ford, Craig Robson, Daniel Temple, and Michael Gerlach “Metrics for scene change detection in digital video sequences” Multimedia Computing and Systems '97. Proceedings., IEEE International Conference on , 1997. Page(s): 610 —611
[22] Mee-Sook Lee; Bon-Woo Hwang; Sanghoon Sull; Seong-Whan Lee “Automatic video parsing using shot boundary detection and camera operation analysis” Pattern Recognition, 1998. Fourteenth International Conference Proceedings, Volume: 2 , 1998. Page(s): 1481 -1483 vol.2
[23] Yueting Zhuang, Yong Rui, Thomas S. Huang, and Sharad Mehrotra, "Adaptive key frame extraction using unsupervised clustering," in Proceedings of IEEE International Conference on Image Processing, Chicago, IL, October 4-7 1998.
[24] P. O. Gresle and T. S. Huang. “Gisting of video documents: A key frames selection algorithm using relative activity measure”. In The 2nd International Conference on Visual Information Systems, 1997.
[25] Di Zhong, Hong Jiang Zhang and Shih-Fu Chang, “Clustering Methods for Video Browsing and Annotation”, SPIE Proceedings, vol. 2670, 1996 pp. 239-246.
[26] Wolf, W. “Key frame selection by motion analysis” Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on , Volume: 2 , 1996. Page(s): 1228 -1231 vol. 2
[27] Giridharan Iyengar and Andrew B. Lippman “Semantically controlled content-based retrieval of video” Multimedia Storage and Archiving III, Voice, Video and Data 98, Boston, November 1998.
[28] E. Ardizzone and M. La Cascia. “Video indexing using optical flow field”. International Conference on Image Processing, volume 3, 1996, pages 831-34
[29] Wallace Martin, “Recent theories of narrative” chapter 5 Cornell University Press, Ithaca, NY, USA, first ed., 1986
指導教授 范國清(Kuo-Chin Fan) 審核日期 2000-7-11
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