Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/9262
標題: 建立應用於二次曲面螢幕之投影機陣列
Constructing the Projector Matrix for Quadratic Curved Screens
作者: 曾俊瑋
Tseng, Chun-Wei
關鍵字: 影像幾何修正;Image Geometry Correction;影像柔邊;投影機陣列;二次曲面螢幕;Edge Blending;Projector Matrix;Quadratic Curved Screens
出版社: 電機工程學系所
引用: [1]R. Matt Steele, Mao Ye, and Ruigang Yang, "Color calibration of multi-projector displays through automatic optimization of hardware settings,"Computer Vision and Pattern Recognition Workshops, pp.55-60, 2009. [2]P. Bourke, “Edge blending using commodity projectors,” http://paulbourke.net/texture_colour/edgeblend/, 2004. [3]T. Moriya, F. Beniyama, K. Utsugi, T. Minakawa, H. Takeda, andK. Ando, “Multi-camera and multi-projector based seamless live imagedisplay system,” Proceedings of the International Multimedia Modelling Conference, pp. 265–272, 2004. [4]M. Harville, B. Culbertson, I. Sobel, D. Gelb, A. Fitzhugh, and D.Tanguay, “Practical Methods for Geometric and Photometric Correction of Tiled Projector Displays on Curved Surfaces”, Computer Vision and Pattern Recognition Workshop, pp. 5-5, 2006. [5]Y.-M. Chuang, S.-P. Hsu, K.-C. Huang, Y.-C. Chang, and S.-H. Ruan,“Implementation of image warping with application to projection onto a curved display,” Proceedings of the IEEE Conference on Industrial Electronics and Applications, pp. 404–408, 2010. [6]Y.-M. Chuang, S.-P. Hsu, and Y.-C. Chang, “Image warping implemented by a simple array of projectors,” Proceedings of the IEEE Conference on Industrial Electronics and Applications, pp. 620–624, 2011. [7]A. Majumder, Zhu He, H. Towles, G. Welch, “Achieving color uniformity across multi-projector displays,”Visualization Proceedings, pp.117-124, 2000. [8]E. S. Bhasker and A. Majumder, “Geometric modeling and calibration of planar multi-projector displays using rational bezier patches,” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8, 2007. [9]R. Raskar, G. Welch, and H. Fuchs, “Seamless projection overlaps using image warping and intensity blending,” Proceedings of the Fourth International Conference on Virtual Systems and Multimedia, 1998. [10]T. Milliron, R. J. Jensen, R. Barzel, and A. Finkelstein, “Aframework for geometric warps and deformations,” ACM Transactions on Graphics, vol. 21, pp. 20–51, 2002. [11]B. Sajadi, M. Lazarov, M. Gopi, and A. Majumder, “Color seamlessness in multi-projector displays using constrained gamut morphing,” IEEE Transactions on Visualization and Computer Graphics, vol. 15, no. 6, pp. 1317–1326, 2009. [12]F. L. Bookstein, “Principal warps: thin plate splines and the decomposition of deformations,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, pp. 567–585, 1989. [13]L. G. Brown, “A survey of image registration techniques,” ACM Computing Surveys, vol. 24, no. 4, pp. 325–376, 1992. [14]C. A. Glasbey and K. V. Mardia, “A review of image warping methods,”Journal of Applied Statistics, vol. 25, pp. 155–171, 1998. [15]H. Chen, R. Sukthankar, G. Wallace, and K. Li, “Scalable alignment of large-format multi-projector displays using camera homography trees,” Visualization, 2002. VIS 2002. IEEE, pp. 339–346, 2002. [16]Y. T. Tang and C. Y. Suen, “Image transformation approach to nonlinear shape restoration,” IEEE Transactions on Systems, Man and Cybernetics, vol. 23, pp. 155–171, 1993 [17]R. Raskar, J. V. Baar, P. Beardsley, T. Willwacher, S. Rao, and C. Forlines, “iLamps: Geometrically aware and self-configuring projectors,” ACM Transactions on Graphics, vol. 22, pp. 809–818, 2003. [18]B. Sajadi and A. Majumder, “Auto-calibration of cylindrical multi-projector systems,” IEEE Virtual Reality Conference, pp. 155–162, 2010. [19]T. Takahashi, N. Numa, T. Aoki, and S. Kondo, “A geometric correction method for projected images using sift feature points,” Proceedings of the 5th ACM/IEEE International Workshop on Projector camera systems, no. 4, 2008. [20]M. Ashdown, M. Flagg, R. Sukthankar, and J. Rehg, “A flexible projector-camera system for multi-planar displays,” Proceedings of the 2004 IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 165–172, 2004.
摘要: 
近年來投影機技術日新月異,投影機已經從過去的CRT(Cathode Ray Tube)投影機演進到目前的DLP(Digital Light Processing)投影機。除了將投影機的體積大幅縮小,也提升了投影畫面的解析度與流明。由於投影機具有高解析度、可以調整投影畫面尺寸與可攜性等特性,所以使投影機的應用越來越普及。然而在一些應用上為了創造寬闊的視野,會將投影畫面呈現在曲面螢幕上。但投影在曲面螢幕時,會因為投影畫面各部分的投影距離不同,而產生影像扭曲的問題。由於目前解決問題的方式所需要的成本都太高,所以本研究提出一個簡單的演算法並利用低成本的硬體解決影像扭曲的問題。
本文第一章首先介紹目前的影像幾何修正系統與多投影機陣列所面臨的問題,以及現行解決問題的方法。經過分析後針對這些方法的缺點提出本研究的改進方式。
第二章介紹本研究所使用的相關技術,由於多投影機陣列之投影畫面在拼接時,為了方便將投影畫面拼接,會將畫面的一部分重疊。然而重疊的部分會因影像重疊出現亮帶,所以本研究利用影像柔邊技術來修正此問題。
第三章探討將投影機陣列應用在二次曲面螢幕時會出現的影像形變問題,並針對此問題推導出對應的影像幾何修正演算法。第四章將影像幾何修正演算法化簡,縮短演算法的運算時間。
第五章將比較演算法在簡化前和簡化後的演算法複雜度與建立新舊座標轉換關係表的執行時間。最後透過2x2投影機陣列投影在二次曲面螢幕的實驗,驗證影像幾何修正演算法的正確性。在第六章中總結研究結果並提出未來可以改進的地方。

In recent years, projector technology has developed rapidly, evolving from CRT(Cathode Ray Tube)to DLP(Digital Light Processing)projectors. In addition to decreasing substantially in projector size, projectors have improved in resolution and the luminance of the projected image. Because DLP projectors have high resolution and portability, and allow users to adjust the size of the projected image, they have become increasingly popular. In some applications, images will project onto curved screen to create a wide field of view. Since the screen is not planar, the projection of the image is distorted. The current solutions to image distortion are costly; thus, the study proposes using a simple algorithm and low-cost hardware to ameliorate the problem.
Chapter 1 introduces the image geometry correction system and multi-projector matrix, including the current problems and solutions regarding their use. After analyzing the advantages and disadvantages of various solutions, additional improvements are suggested.
The techniques used in this study are discussed in Chapter 2. To conveniently tile projected images, multi-projector matrices overlap part of the projected image; however, the overlap region appears as a bright seam. Image edge blending technology was used to fix this problem.
Chapter 3 presents the distortion of images projected onto quadric screens and a geometric correction algorithm was developed to solve this problem. In Chapter 4, the image geometry correction algorithm is simplified and its execution time is shortened.
Chapter 5 presents a comparison on the complexity of the algorithm before and after simplifying the algorithm, and also compares the executing time of building the lookup table before and after simplifying the algorithm. Finally, a 2x2 projector matrix was used, projecting an image onto a quadratic curved screen to verify the accuracy of the geometric correction algorithm. The final chapter presents a summary of the experimental results, providing recommendations for future research.
URI: http://hdl.handle.net/11455/9262
其他識別: U0005-3007201305025000
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