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研究生:張芸菁
研究生(外文):Yun-Ching Chang
論文名稱:利用移動向量資訊同步立體視頻之階層演算法
論文名稱(外文):A COARSE-TO-FINE ALGORITHM FOR SYNCHRONIZING STEREO VIDEO SEQUENCES USING MOTION INFORMATION
指導教授:周俊賢周俊賢引用關係
指導教授(外文):Chun-Hsien Chou
口試委員:周俊賢
口試委員(外文):Chun-Hsien Chou
口試日期:2013-07-18
學位類別:碩士
校院名稱:大同大學
系所名稱:通訊工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2013
畢業學年度:101
語文別:中文
論文頁數:48
中文關鍵詞:立體視頻序列移動向量場區塊匹配估計相對應移動軌跡分層搜尋
外文關鍵詞:synchronization stereo videodisparity estimationmotion estimationstereo video system
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近年來隨著科技的進步以及3D電影的風行加速了平面顯示技術的突破,3D已在全球掀起一股熱潮,在3D立體顯示設備及顯示技術的提供能與時並進方能給予立體顯示系統一個完整的市場。因此隨著立體顯示器技術日益進步,以及立體顯示裝置的研究之普及,另一個重點在於3D內容的來源不可缺少。
   雖然目前市面上已經有少數的3D立體拍攝系統能夠提供3D立體內容,然而其價格以及使用上不夠便利因此尚未能普及化,對於現今的市場需求而言3D內容來源仍不夠充足,而提供3D視訊是未來最俱發展潛力的市場。
在3D電影與電玩之中,當拍攝巨觀的場景畫面時會使用Hyperstereo的方式來作拍攝,而這種拍攝方式通常使用兩部獨立之攝影機作拍攝,因此存在一個問題,即一對立體影片之間的畫面時序同步問題。
本論文中提出一個在非同步時間下之雙鏡頭立體影像找出兩部視訊之同步,在所提出之演算法部分,立體視訊特有的視差關係配合移動向量所計算出的視差像量差,找出視訊的同一時間點。本研究的目的在利用非經過系統校正拍攝之雙部攝影機自製影片之同步校正問題解決,藉由此論文提出的演算法,使得人人都有可能利用一般攝影機自製拍攝出立體視頻。
With the fast progress in 3D display technology, stereoscopic contents are also
growing fast and getting increasingly important. However, some problems may occur during the production of stereoscopic contents, such as the determination of stereo bases for scenes of different depths, false parallax, and the synchronization of two video sequences captured from two independent cameras. This thesis addresses on how to synchronize the left-eye-view and right-eye-view video sequences which are not synchronized for healthy and comfortable viewing of stereoscopic videos. The research involves the development of a coarse-to-fine algorithm that employs the motion field information for finding the trajectory correspondence between two sequences to be synchronized. In the algorithm, motion fields are obtained by means of full-search block matching motion estimation. Through a hierarchical search of similar motion field information, the trajectory correspondence can be found in low computational
complexity. Simulation results indicate that the proposed algorithm is able to
synchronize stereo video sequences of various types in a short latency of time.
誌謝 I
摘要 II
ABSTRACT III
目錄 IV
圖目錄 VI
表目錄 VIII
第一章 緒論 1
1.1立體影像技術的發展 1
1.2 研究背景 4
1.3 研究動機與目的 6
1.4 論文架構 8
第二章 文獻探討 9
2.1 人類視覺感知 9
2.1.1 視差定義 11
2.1.2 視差估計 13
2.1.3 移動估計 15
2.2 移動向量資訊 17
2.2.1 移動向量 17
2.2.2 方塊比對演算法(Block-matching algorithm) 18
2.3視訊序列同步 19
2.3.1 基於圖像特徵匹配法( Feature-based image matching ) 20
2.3.2 基於序列特徵匹配法(Feature-based sequence matching ) 22
第三章 階層式演算法 24
3.1移動向量資訊 28
3.1.1移動向量場 29
3.2 利用移動向量資訊同步立體影像之分層演算法 31
3.2.1 初步定位搜尋 33
3.2.2移動資訊場之分層比對 38
第四章 模擬結果 40
4.1模擬環境 40
4.2 模擬條件 42
4.3 實驗結果 43
第五章 結論與未來展望 46
參考文獻 47
[1]The first stereo painting in the world, http://www.3d-historisch.de
[2]The first stereo picture, http://www.stereoviews.com/
[3]D. Fleet, A. Jepson ,and M. Jenkin, “Phase-based Disparity Measurement,”
Computer Vision, Graphics, and Image Processing: Image Understanding,1991, pp.198-210.
[4]S. Chien, S. Yu, L. Ding, Y. Huang, and L. Chen, “Fast Disparity
Estimation Algorithm for Mesh-based Stereo Image/Video Compression with Two-stage Hybrid Approach,” Visual Communications and Image Processing 2003, June 2003, pp.1521-1530.
[5]C.–Y. Hsu and Y.–P. Huang, “Development and Researches of Real 3D Display Technologies,” Photonic Eng., 2007, pp.53-60.
[6]R. Thoma and M. Bierling, “Motion Compensating Interpolation Considering Covered and Uncovered Background,” Vol.1, Signal Processing: Image Communication, 1989, pp.191-212.
[7] S. Han and J. Woods, “Frame-Rate Up-Conversion Using Transmitted Motion and Segmentation Fields for Very Low Bit-Rate Video Coding,” vol.1, IEEE International Conference on Image Processing, 1997, pp.747-750.
[8] Y. Caspi and M. Irani, “A step towards sequence-to-sequence alignment,” CVPR pp. 682-689, 2000.
[9] Y. Caspi, D. Simakov, and M. Irani, “Feature-based sequence-to-sequence matching,” VAMODS workshop,2002
[10] Tinne Tuytelaars1 and Luc Van Gool, “Synchronizing Video Sequences,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004
[11] Michael Bleyer and Margrit Gelautz, “Temporally Consistent Disparity Maps from Uncalibrated Stereo Videos,” International Symposium on Image and Signal Processing and Analysi ,2009
[12]A. Redert, E.Hendriks ,and J.Biemond, “Correspondence Estimation in Image
Pairs,” vol.16, IEEE Signal Processing Magazine, May 1999, pp. 29–46.
[13]T. Tuytelaars, L. Van Gool, L. Dhaene and R. Koch, “Matching Affinely Invariant Regions for Visual Servoing,” IEEE Conference on Robotics and Automation, pp. 1601-1606,1999.
[14] T. Tuytelaars and L. Van Gool Wide Baseline Stereo based on Local, “ Affinely invariant Regions, ” British Machine VisionConference, pp. 412-422, 2000.
[15]M. Accame, F. Natale, and D. Giusto, “Hierarchical Block Matching for Disparity Estimation in Stereo Sequences,” Vol.2, International Conference on Image Processing, Oct.1995, pp.374-377.
[16]T. Ha, S. Lee and J. Kim, “Motion Compensated Frame Interpolation by New Block-Based Motion Estimation Algorithm,” Vol.50, no.2, IEEE Transactions on Consumer Electronics, 2004, pp.752-759.
[17] M. Bierling, “Displacement Estimation by Hierarchical Block-Matching,” vol.1001 Visual Communication and Image Processing, 1998, pp.942–951.
[18]M. Accame and F.-G.De Natale, and D.-D. Giusto, “Hierarchical Block Matching for Disparity Estimation in Stereo Sequences,” vol.2, International Consortium for Intergenerational Programmes, 1995, pp.374–377.
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