期刊文献+

立体图像的遮挡边界区域检测技术 被引量:1

A detection technique of occluded boundary regions for stereo image pairs
下载PDF
导出
摘要 针对平行结构立体摄像机存在较大的遮挡边界区域问题,本文提出了一种基于可信图的遮挡边界检测算法。首先通过采样计算立体图像对中几条扫描线的可信值,从而得到遮挡边界的若干采样点;然后通过RANSAC算法得到遮挡边界。理论和实验分析表明该算法对复杂背景的立体图像有好的检测精度;对人肩像等简单背景图像的检测精度不好,但通过校正后仍可得到较准确的遮挡边界。 Aimed at the presence of large occluded regions in stereo image pairs obtained from stereo camera pairs, an algorithm which can detect occluded boundary areas based on reliability map is proposed. Firstly, a number of sampled occluded boundary points are obtained by calculating reliability of the disparity on the corresponding sampled scan lines. Secondly, the boundary llne is calculated by RANSAC method. Theoretical and experimental analyses showed that the proposed algorithm gives a good boundary detection accuracy for stereo images with complex backgrounds. But for stereo images with homogenous background, the results are not good, however, the algorithm can also give a relatively good accuracy after certain correction.
出处 《中国体视学与图像分析》 2008年第1期17-20,共4页 Chinese Journal of Stereology and Image Analysis
基金 国家自然科学基金资助项目(No.60472083)
关键词 边界区域检测 视差估计 立体图像编码 detection boundary region disparity estimation stereo image coding
  • 相关文献

参考文献7

  • 1Malassiotis S, Strintzis M G. Joint motion/disparity MAP estimation for stereo image sequences [ A ], Proc Inst Electr [C]. Eng 1996, 143(2):101-108.
  • 2Tzovaras D, Grammalidis N, Strintzis M G. Disparity field and depth map coding for muhiview 3D image generation [J]. Signal processing Image Communication, 1998, 11 (3) :205 -230.
  • 3刘莉,姜志国,谢凤英,陈进.光学体视显微图像立体测量系统研究与开发[J].中国体视学与图像分析,2003,8(4):220-224. 被引量:9
  • 4Wang R, Wang Y. Muhiview video sequence analysis, compression, and virtual viewpoint synthesis [ J]. IEEE Trans Circ Sys Video Technol, 2000, 10 ( 3 ) : 397 - 410.
  • 5Park J H, Park H W. A mesh-based disparity representation method for view interpolation and stereo image compression [ J] , IEEE Trans Image Processing, 2006, 15(7) :1751 - 1762.
  • 6Fan H, Ngan K N, Disparity map coding based on adaptive triangular surface modeling [ J]. Signal Process Image Communication,1998, 14(2) :119 - 130.
  • 7薛健,张兆田,熊晓芸,李慧,田捷.工业过程断层图像的三维动态可视化[J].中国体视学与图像分析,2005,10(3):183-188. 被引量:1

二级参考文献18

  • 1谢凤英,姜志国.基于互相关的显微医学图像配准[J].中国体视学与图像分析,2001,6(3):175-178. 被引量:9
  • 2朱平,陈丙森.基于特征的扫描电镜立体对三维重建[J].电子显微学报,1997,16(1):49-56. 被引量:5
  • 3游素亚.立体视觉研究的现状与进展[J].中国图象图形学报(A辑),1997,2(1):17-24. 被引量:101
  • 4S Liu,L Fu,W Q Yang.Optimization of an iterative image reconstruction algorithm for electrical capacitance tomography[J].Measurement Science and Technology,1999,10(7):L37-L39.
  • 5S Liu,L Fu,W Q Yang,et al.Prior iteration for image reconstruction with electrical capacitance tomography[J].IEE Proc Sci Meas Technol,2004,151:195-200.
  • 6Mingchang Zhao,Jie Tian,Xun Zhu,et al.The design and implementation of a C++ toolkit for integrated medical image processing and analyzing[C].Proceedings of SPIE Medical Imaging 2004,2004,5367.39-47.
  • 7Marc Levoy.Efficient ray tracing of volume data[J].ACM Transactions on Graphics,1990,9(3):245-261.
  • 8Marc Levoy.A hybrid ray tracer for rendering polygon and volume data[J].IEEE Computer Graphics and Applications,1990,10(2):33-40.
  • 9W Q Yang,D M Spink,T A York,et al.An image-reconstruction algorithm based on Landweber's iteration method for electrical-capacitance tomography[J].Measurement Science and Technology,1999,10(11):1065-1069.
  • 10W Q Yang,Lihui Peng.Image reconstruction algorithms for electrical capacitance tomography[J].Measurement Science and Technology,2003,14:R1-R13.

共引文献8

同被引文献13

  • 1孔明,王式民.共轴法立体视觉三维测量的研究[J].计量学报,2004,25(4):294-297. 被引量:10
  • 2Toh P S, Forrest A K. Occlusion detection in early vision [C]// Proceedings of 3rd International Conference onComputer Vision, Piscataway, USA,1990, 126 - 132.
  • 3Ince S, Konrad J. Geometry-based estimation of occlusions from video frame pairs [ C ]/! Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Piscataway, USA, 2005,II 933 - 936.
  • 4Stein A N, Hebert M. Local detection of occ|usion boundaries in video [ J ]. Image and Vision Computing, 2009,27(5) :514 -522.
  • 5Stein A N, Hebert M. Occlusion boundaries from motion: Low-level detection and mid-level reasoning [ J ]. International Journal of Computer Vision, 2009,82 ( 3 ) : 325 - 357.
  • 6Sargin M E, Bertelli L, Manjunath B S, et al. Probabilistic occlusion boundary detection on spatio- temporal lattices [ C ]/! Proceedings of the IEEE International Conference on Computer Vision, Piscataway, USA,2009,560-657.
  • 7He X, Yuille A. Occlusion boundary detection using pseudo-depth [ C ]// Proceedings of the European Conference on Computer Vision, Heidelberg, Germany: Springer Verlag, 2010,539 - 552.
  • 8Sundberg P, Brox T, Maire M, et al. Occlusion boundary detection and figure/ground assignment from optical flow [ C ]// Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Piscataway, USA,2011,2233-2240.
  • 9Jacobson N, Freund Y, Nguyen T Q. An online learning approach to occlusion boundary detection [ J ]. IEEE Transactions on Image Processing, 2012,21 ( 1 ) : 252 - 261.
  • 10Chen D, Yuan Z, Zhang G, et al. Detecting occlusion boundaries via saliency network [ C ]/! Proceedings of International Conference on Pattern Recognition, Piscataway, USA, 2012,2569 - 2572.

引证文献1

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部