摘要: 散斑相关算法可以用来估计场景的深度信息,但因易受到噪声干扰且计算量大而难以应用在基于普通计算机的三维重建系统中。采取零均值归一化互相关函数(ZNCC)作为相关算法的匹配代价函数,对传统的ZNCC快速计算方法进行修改并将其应用于计算机的通用图形处理器(GPU),实现了实时的场景三维重建效果。对比实验表明,在精度一致的前提下,提出的GPU计算方法的速度是CPU算法的39倍。
[1] Schaffer M,Kowarschik G M.High-speed pattern projection for three-dimensional shape measurement using laser speckles[J].Applied optics,2010,9(10):3622-3629 [2] Barrientos B,Cerca M,Garcia-Ma R J.Three-dimensional displacement fields measured in a deforming granular-media surface by combined fringe projection and speckle photography[J].Journal of Optics A:Pure and Applied Optics,2008,0(10):104027 [3] Yang Rui-gang,Pollefeys M.Multi-resolution real-time stereoon commodity graphics hardware[C]∥IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Madison,2003:211-217 [4] Yang R G,Pollefeys M,Li S F.Improved real-time stereo on commodity graphics hardware[C]∥IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshop.Washington,2004:36-36 [5] Hirschmuller H,Scharstein D.Evaluation of stereo matchingcosts on images with radiometric differences[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2009,31(9):1582-1599 [6] Chen F,Brownm G,Song M.Overview of three-dimensionalshape measurement using optical methods[J].Optical Enginee-ring,2000,39(1):10-22 [7] Batlle J,Salvi M E.Recent progress in coded structured light as a technique to solve the correspondence problem:a survey[J].Pattern recognition,1998,1(7):963-982 [8] Stockman H G.3-D surface solution using structured light and constraint propagation[J].IEEE Transactions on Pattern Analy-sis and Machine Intelligence,1989,11(4):390-402 [9] Smisek J,Jancosek M,Pajdla T.3D with Kinect[M].German:Springer,2013:3-25 [10] Wang G,Yin X,Pei X.Depth estimation for speckle projection system using progressive reliable points growing matching[J].Applied Optics,2013,2(3):516-524 [11] Gong M,Yang R,Wang L.A performance study on different cost aggregation approaches used in real-time stereo matching[J].International Journal of Computer Vision,2007,5(2):283-296 [12] Arieli Y,Freedman B,Machline M.Depth mapping using projected patterns:U.S.Patent 8150142[P].2012-4-3 [13] Faugeras O,Hotz B,Mathieu H.Real time correlation-basedstereo:algorithm,implementations and applications[R].INRIA,1993 [14] Bay H,Tuytelaarsl T,Gool V.Surf:Speeded up robust features[M].German:Springer Berlin Heidelberg,2006:404-417 [15] Hallers I,Nedevschi S.Design of interpolation functions for subpixel-accuracy stereo-vision systems[J].IEEE Transactions on Image Processing,2012,1(2):889-898 [16] 王志国,王贵锦,施陈博.积分图像的快速GPU计算[J].计算机应用研究,2011,28(10):3913-3916 Wang Zhi-guo,Wang Gui-jin,Shi Chen-bo,et al.Fast Integral Image Computation on GPU[J].Journal of Computer Applications,2011,28(10):3913-3916 [17] Harris M,Senguptaj S,Owens J D.Parallel prefix sum(scan) with CUDA[J].GPU gems,2007,39(3):851-876 [18] NVIDIA.NVIDIA C best practices guide.http://clocs.nvidia.com/cuda/pdf/CUDA_C_Best_Practices_Guide.pdf [19] Mei X,Sun X,Zhou M.On building an accurate stereo matching system on graphics hardware[C]∥2011 IEEE International Conference on Computer Vision Workshops(ICCV Workshops).2011:467-474 [20] Bilgic B,Horn B K P,Masaki I.Efficient integral image computation[C]∥Intelligent Vehicles Symposium(IV) on the GPU.2010 IEEE,2010:528-533 [21] NVIDIA.Nvida cuda compute unified device architecture programming guide.http://moss.csc.nscu.edu/~mueller/cluster/nvidia/2.0/Programming_Guide_2.0Beta2.pdf [22] Ortega J S.Towards visual localization,mapping and moving objects tracking by a mobile robot:a geometric and probabilistic approach[D].Toulonse:Institut National Polytechnique de Toulouse-INPT,2007 [23] 汤颖,肖廷哲,范菁.基于GPU加速的快速图像相似区域查找[J].计算机科学,2014,41(2):290-296 Tang Ying,Xiao Ting-zhe,Fan Jing.GPU-based Fast Search of Similar Patches in Images[J].Computer Science,2014,41(2):290-296 [24] 党建武,杭利华,王阳萍,等.基于GPU的2D-3D医学图像配准[J].计算机科学,2013,40(4):306-309Dang Jian-wu,Hang Li-hua,Wang Yang-ping,et al.2D-3D Medi-cal Image Registration Based on GPU[J].Computer Science,2013,40(4):306-309 |
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