计算机科学 ›› 2021, Vol. 48 ›› Issue (1): 204-208.doi: 10.11896/jsjkx.191000205
桑苗苗1, 彭进先2, 达通航1, 张旭峰1
SANG Miao-miao1, PENG Jin-xian2, DA Tong-hang1, ZHANG Xu-feng1
摘要: 近年来双目立体匹配技术发展迅速,高精度、高分辨率、大视差的应用需求无疑对该技术的计算效率提出了更高的要求。由于传统立体匹配算法固有的计算复杂度正比于视差范围,已经难以满足高分辨率、大视差的应用场景。因此,从计算复杂度、匹配精度、匹配原理等多方面综合考虑,提出了一种基于PatchMatch的半全局双目立体匹配算法,在路径代价计算过程中使用空间传播机制,将可能的视差由整个视差范围降低为t个候选视差(t远远小于视差范围),显著减少了候选视差的数量,大幅提高了半全局算法的计算效率。对KITTI2015数据集的评估结果表明,该算法以5.81%的错误匹配率和20.2 s的匹配时间实现了准确性和实时性的明显提高。因此,作为传统立体匹配改进算法,该设计可以为大视差双目立体匹配系统提供高效的解决方案。
中图分类号:
[1] WANG W T,HAN Z G,LIU P F.Multi-sensor Image Registration Algorithm Based on SIFT Points and Canny Edge Features Matching[J].Computer Science,2011,38(7):287-289. [2] XU Z G,CHEN C.Robust and Fast Feature Points Matching[J].Computer Science,2013,40(2):294-296. [3] MOZEROV M G,WEIJER J.Accurate Stereo Matching byTwo-Step Energy Minimization[J].IEEE Transactions on Ima-ge Processing,2015,24:1153-1163. [4] ZHAN Y,GU Y,ZHANG K C,et al.Accurate image-guided stereo matching with efficient matching cost and disparity refinement[J].IEEE Transactions on Circuits and Systems for Video Technology,2015,99:11. [5] HIRSCHMULLER H.Accurate and efficient stereo processing by semi-global matching and mutual information[C]//IEEE Conference on Computer Vision and Pattern Recognition.2005:807-814. [6] HIRSCHMULLER H,SCHARSTEIN D.Evaluation of costfunctions forstereo matching[C]//IEEE Conference on Compu-ter Vision and Pattern Recognition.2007:1-8. [7] KENDALL A,MARTIROSYAN H,DASGUPTA S,et al.End-to-End Learning of Geometry and Context for Deep Stereo Regression[C]//IEEE International Conference on Computer Vision.2017:66-75. [8] ZBONTAR J,LECUN Y,et al.Stereo matching by training a convolutional neural network to compare image patches[J].Journal of Machine Learning Research,2016,17(2):1-32. [9] SEKI A,POLLEFEYS M.SGM-Nets:Semi-global matchingwith neural networks[C]//IEEE Conference on Computer Vision and Pattern Recognition Workshops.2017:21-26. [10] BARNES C,SHECHTMAN E,FINKELSTEIN A,et al.PatchMatch:A randomized correspondence algorithm for structural image editing[J].ACM Transactions on Graphics,2009,28(3):24-28. [11] TTOFIS C,KYRKOU C,THEOCHARIDES T.A low-cost real-time embedded stereo vision system for accurate disparity estimation based on guided image filtering[J].IEEE Transactions on Computers,2016,65(9):2678-2693. [12] CHEN S Q,ZHANG X C,SUN H B,et al.sWMF:Separable weighted median filter for efficient large-disparity stereo matching[C]//IEEE International Symposium on Circuits and Systems.2017:1-4. [13] BLEYER M,RHEMANN C,ROTHER C.Patchmatch stereo-stereo matching with slanted support windows[C]//Machine Vision Conference.2011:1-11. [14] BESSE F,ROTHER C,FITZGIBBON A W,et al.PMBP:Patchmatch belief propagation for correspondencefield estimation[J].International Journal of Computer Vision,2014,110(1):2-13. [15] MENZE M,GEIGER A.Object scene flow for autonomous vehicles[C]//IEEE Conference on Computer Vision and Pattern Recognition.2015:3061-3070. [16] SCHARSTEIN D,HIRSCHMÜLLER H,KITAJIMA Y,et al.High-resolution stereo datasets with subpixel accurate ground truth[C]//German Conference on Pattern Recognition.2014:31-42. [17] AN W,FANGRONG W,BAICANG G,et al.Disparity map optimization based on edge detection[J].Computer Applications and Software,2019,36(7):236-241. |
[1] | 赵涛, 张凌浩, 赵其刚, 王红军. 基于聚类簇中心的共识跨链交换模型 Accross Block Chain Consensus Transation Model Based on Cluster Center 计算机科学, 2019, 46(11A): 557-561. |
[2] | 曹芳,朱永康. 基于SFS方法的三维重构及精度分析 3D Reconstruction Based on SFS Method and Accuracy Analysis 计算机科学, 2017, 44(Z6): 244-247. https://doi.org/10.11896/j.issn.1002-137X.2017.6A.056 |
|