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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 顏家鈺 | |
| dc.contributor.author | Pei-Jr Wu | en |
| dc.contributor.author | 吳沛芝 | zh_TW |
| dc.date.accessioned | 2021-06-16T05:51:35Z | - |
| dc.date.available | 2016-08-12 | |
| dc.date.copyright | 2014-08-12 | |
| dc.date.issued | 2014 | |
| dc.date.submitted | 2014-08-08 | |
| dc.identifier.citation | 1. Adelson, E.H., & Bergen, J. R., The Plenoptic Function and the Elements of Early Vision. Computational Models of Visual Processing, 1991: p. 3-20.
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Ren Ng, M.L., Mathieu Bredif, Gene Duval Mark Horowitzm and Pat Hanrahan, Light Field Photography with a Hand-Held Plenoptic Camera. 2005-02: Stanford University Computer Science Tech Report CSTR. 9. Georgiev, T.a.L., A, Focused Plenoptic Camera and Rendering. Electronic Imag- ing 19(2), 2010. 10. Levin, A., Fergus, R., Durand, F., and Freeman, W. , Image and Depth from a Conventional Camera with a Coded Aperture. SIGGRAPH, 2007. 11. Subbarao, M., Parallel Depth Recovery by Changing Camera Parameters. Proc. Second Int. Conf. Comput. Vision, 1988: p. 149-155. 12. Nayar S. K. , W.M., Noguchi M. , Real-Time Focus Range Sensor, in Proceedings of the Fifth International Conference on Computer Vision. 1995. p. 995. 13. Lippmann, G., La photographie integrale. Comptes-Rendus, Academie des Sciences 146, 1908: p. 446-551. 14. Donald G. Dansereau, O.P., and Stefan B. Williams, Decoding, Calibration and Rectification for Lenselet-Based Plenoptic Cameras, in IEEE. 2013: CVPR. p. 1027-1034. 15. Ng, R., Digital Light Field Phptography, in computer science. 2006-7, stanford university. p. 203. 16. Robert C. BOLLES, H.H.B., and David H. Marimont, Epipolar-Plane Image Analysis: An Approach to Determining Structure from Motion. Computer Vision and Image Understanding, 1987: p. 7-55. 17. Isaksen, A., McMillan, L., and Gortler, S. J, Dynamically Reparameterized Light Fields Siggraph 2000, Computer Graphics Proceedings 2000: p. 297-306. 18. Agarwala, A., Dontcheva, M., Agrawala, M., Drucker, S., Colburn, A., Curless, B., Salesin, D., and Cohen, M, Interactive Digital Photomontage. Transactions on Graphics (Proceedings of siggraph 2004), 2004: p. 292-300. 19. Stroebel, L., Compton, J., Current, I., and Zakia, R, Photographic Materials and Processes. Boston: Focal Press, 1986. 20. Levoy, M., Chen, B., Vaish, V., Horowitz, M., McDowall, I., and Bolas, M., Synthetic aperture confocal imaging. acm Transactions on Graphics (Proceedings of siggraph 2004), 2004. 23(3): p. 822-831. 21. Bracewell, R.N., Strip integration in radio astronomy. Aust. J. Phys., 1956: p. 198-217. 22. Wertheimer, M., Laws of organization in perceptual forms (partial translation). A sourcebook of Gestalt Psychology, 1938: p. 71-88. 23. Pedro F. Felzenszwalb, a.D.P.H., Efficient Graph-Based Image Segmentation. International Journal of Computer Vision, 2004-09. 59(2): p. 167-181. 24. Weiss, Y., Segmentation using Eigenvectors. Proceedings of the International Conference on Computer Vision (2), 1999: p. 975-982. 25. Criminisi, A., et al., Extracting layers and analyzing their specular prpperties using epipolar-plane-image analysis. Computer Vision and Image Understanding, 2005-01. 97(1): p. 51-85. 26. Martin Matousek, T.W., and Vaclav Hlavac, Accurate correspondences from epipolar ˇ plane images. Computer Vision Winter Workshop, 2001-02: p. 181-189. 27. Dragotti., J.B.a.P., Segmentation of epipolar-plane image volumes with occlusion and disocclusion competition. IEEE 8th Workshop on Multimedia Signal Processing, 2006: p. 182-185. 28. Bigun, J.a.G.G. Optimal Orientation Detection of Linear Symmetry. in Proceedings of the 1st International Conference on Computer Vision. 1987-06. London, England. 29. Gong, D.C., Tangxiaotao, Z., The Transformation from Tilted Image to Horizontal Image Based on the Rational Function Model, in XXII Congress of the International Society for Photogrammetry, Remote Sensing. 2012: Melbourne, Australia. p. 3. 30. Forstner W., a.G.E., A fast Operator for Detection and Precise Location of Distinct Points, Corners and Centers of Circular Features. ISPRS Intercommission Workshop, 1987-06. 31. Wanner S., G.B., Variational Light Field Analysis for Disparity Estimation and Super Resolution. IEEE TPAMI, 2013. 32. Brox T. , R.M., Deriche R., Weicket J., Unsupervised Segmentation Incorporating Colour, Texture, and Motion. Image Processing and Computer Vision, 2003: p. 353-360. 33. Keeling S. L., S.R., Nonlinear anisotropic diffusion filters for wide range edge sharpening. Proc. SPIE 3979, Medical Imaging 2000: Image Processing, 1309, 2002: p. 175-190. 34. Brox T. , W.J., Burgeth B., Mrazek P., Nonlinear Structure Tensors. Image and Vision Computing, 2005. 24: p. 41-55. 35. Tschumperle, D., Deriche, R., Diffusion Tensor Regularization with Constraints Preservation. Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on 2001. 1: p. 948-953. 36. J., W., Anisotropic Diffusion in Image Processing. 1998. 37. Kaiming, H., Jian, S., Xiaoou, T., Guided Image Filtering. IEEE 2013. 35: p. 1397-1409. 38. Chen. C., L.H., Yu. A., Kang S. B., Yu. J. , Light Field Stereo Matching Using Bilateral Statistics of Surface Cameras. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2014. 39. Levin, A., Lischinski, D., and Weiss, Y., Colorization using optimization. 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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/56836 | - |
| dc.description.abstract | 我們利用積分攝影(integral photography)的概念取得四維光場(light field)，並以此為基礎提出還原景深的演算法。四維光場不同於以往傳統相機所記錄到的影像資訊，他可以記錄到光進入相機時每束光線的方向，並且被使用在場景深度估測、重新對焦等應用上。本研究由市售的光場攝影機Lytro做為影像的來源，其內置入了微透鏡陣列(micro-lens array)只要拍攝單張照片便可得到各個視角的資訊，因此可以利用影像幾何的三角關係將原圖重新排列合成Epipolar plane image，再加以分析得到景深估測的結果。而微透鏡陣列的大小排列情形會影響到四維光場區分為方向解析度和空間解析度時的組成，其中因為Lytro原始的光感測器尺寸和解析度規格較低，使最後擷取出來的方向解析度為7*7，空間解析度為300*300，在原始資訊較不充足的情況下，我們在提出的演算法中加強相關高低階影像處理例如:物體分離(segmentation)可以在進行景深估測前預先知道每個物體的存在，使在估測當下減少誤差的產生;非線性結構張量(nonlinear diffusion)改善了傳統的高斯濾波器造成邊緣模糊的情況，加強物體邊緣資訊的保存，以上方法都使場景深度的估測結果達到較好的抗雜訊效果。 | zh_TW |
| dc.description.abstract | 4D light field offers the necessary information for scene reconstruction. It is thus desirable to use it as a quick mean to obtain three dimensional scene. In this thesis, we first use the concept of integral photography to get the 4D data from the scene. We then propose an algorithm for the depth recovery. The 4D light field is taken with a commercial plenoptic camera from Lytro. The plenoptic camera uses an added micro-lens array which allows us to also record the direction of the incoming beam. Although Lytro uses the lens array information for refocusing, here we use it for depth recovery.
The depth information is recovered by transforming the raw image into an EpiPolar-Image (EPI) and then apply triangular geometry to obtain a preliminary result. This preliminary result is basically too noisy for object extraction. We then apply object segmentation and nonlinear diffusion to achieve useful crisp 3D scene information. Due to the trade-off between directional resolution and spatial resolution, the spatial resolution is only 300*300. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T05:51:35Z (GMT). No. of bitstreams: 1 ntu-103-R01522827-1.pdf: 4571021 bytes, checksum: 95f97eaee011069c328e32203f47eaf9 (MD5) Previous issue date: 2014 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 ii Abstract iii Contents iv List of Figure vii Chapter 1 Introduction 1 1.1 Plenoptic Function 1 1.2 Capture Light Field 3 1.3 Application of 4D Light Field 6 1.4 Thesis Outline 7 Chapter 2 Optical Analysis 8 2.1 Capturing and Recording the Light Field 8 2.1.1 Obtain Light Field by Plenoptic Camera 8 2.1.2 Recording and Computation of Light Field 11 2.1.3 Lens Correction 14 2.2 Optimization of the Directional Resolution 16 2.3 Tradeoff between Spatial Resolution and Directional Resolution 18 2.4 Experimental Setting 20 2.4.1 Specification of the plenoptic camera 20 2.4.2 Flow Chart 20 Chapter 3 Preprocessing of Raw-image 23 3.1 Sub-Aperture Images 23 3.2 Digital Refocusing 26 3.2.1 Related work 26 3.2.2 Image Equation 27 3.2.3 Fourier Slice Theorem and Limitation 30 3.2.4 Result of Digital Refocusing 35 3.3 Image Segmentation 36 Chapter 4 Depth Estimation 40 4.1 Epipolar-Plane Image 40 4.1.1 Related work 41 4.1.2 Geometry of the EPI 43 4.1.3 Limitation of Epipolar Images 45 4.2 Analysis of Light Field Structure 47 4.2.1 Classical Structure Tensor 47 4.2.2 Isotropic Nonlinear Diffusion 48 4.2.3 Anisotropic Nonlinear Diffusion 50 4.3 Experimental Result 52 4.3.1 Local Depth Estimation 52 4.3.2 The Procedure of Experiments 56 Chapter 5 Conclusion and Future Work 59 Reference 60 | |
| dc.language.iso | en | |
| dc.subject | 結構張量 | zh_TW |
| dc.subject | 微透鏡陣列 | zh_TW |
| dc.subject | 四維光場 | zh_TW |
| dc.subject | 景深估測 | zh_TW |
| dc.subject | Light field | en |
| dc.subject | micro-lens array | en |
| dc.subject | structure tensor | en |
| dc.subject | depth estimation | en |
| dc.title | 光場複眼鏡頭應用於機械視覺之場景深度量測方法 | zh_TW |
| dc.title | Analysis of scene reconstruction on machine vision based on light field camera | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 102-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 王富正,鍾添東 | |
| dc.subject.keyword | 四維光場,微透鏡陣列,結構張量,景深估測, | zh_TW |
| dc.subject.keyword | Light field,micro-lens array,structure tensor,depth estimation, | en |
| dc.relation.page | 64 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2014-08-08 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 機械工程學研究所 | zh_TW |
| 顯示於系所單位： | 機械工程學系 | |
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