Stereo Matching Based on Dissimilar Intensity Support and Belief Propagation

被引：3
|
作者：
Da, Feipeng [1 ]
He, Fu [1 ]
Chen, Zhangwen [1 ]
机构：
[1] Southeast Univ, Key Lab Measurement & Control Complex Syst, Minist Educ, Sch Automat, Nanjing 210096, Jiangsu, Peoples R China
来源：
JOURNAL OF MATHEMATICAL IMAGING AND VISION | 2013年 / 47卷 / 1-2期
关键词：
Stereo matching; Local edge detection; Dissimilar intensity support; Belief propagation optimization; Cost aggregation; ALGORITHM; WEIGHT;
D O I：
10.1007/s10851-013-0448-1
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel algorithm based on the window construction method using local edge detection is presented. Firstly, in order to construct the adaptive window, a virtual closed edge is formed around each pixel via second order differential operator. Secondly, a novel rule called Dissimilar Intensity Support (DIS) technique is proposed. This rule is used to distinguish support pixels with dissimilar intensity from those with similar intensity for each centered pixel. So that the performance of window-based cost aggregation computation is improved. Thirdly, belief propagation (BP) optimization algorithm is used to obtain the disparity. The experimental results based on Middlebury stereo benchmark show that the proposed algorithm has good performances.
引用
收藏
页码：27 / 34
页数：8
相关论文
共 50 条
  • [31] Stereo matching by using a new local descriptor based on sign and order in belief propagation algorithm
    Karimi, Hossein
    Dolati, Ardeshir
    Layeghi, Kamran
    DISPLAYS, 2022, 75
  • [32] A New Stereo Matching Method with Combination of Cross-based Aggregation and Hierarchical Belief Propagation
    Yang, Tianyu
    He, Qing
    Wei, Ning
    Li, Baopu
    Hu, Chao
    Meng, Max Q-H.
    PROCEEDING OF THE IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION, 2012, : 379 - 383
  • [33] Stereo matching based on support points
    Zhang, Xue-He
    Zhao, Jie
    Li, Ge
    Hou, Zhen-Xiu
    Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 2015, 23 : 546 - 553
  • [34] Stereo matching based on segmented B-spline surface fitting and accelerated region belief propagation
    Huang, Jingzhou
    IET COMPUTER VISION, 2015, 9 (04) : 456 - 466
  • [35] VLSI Implementation of Belief-Propagation-Based Stereo Matching with Linear-Model Message Update
    Hsiao, Shen-Fu
    Huang, Jun-Ming
    Wu, Po-Sheng
    2014 IEEE ASIA PACIFIC CONFERENCE ON CIRCUITS AND SYSTEMS (APCCAS), 2014, : 73 - 76
  • [36] Accurate Belief Propagation with parametric and non-parametric measure for stereo matching
    Wang, Xiaofeng
    Wang, Hongke
    Su, Yingying
    OPTIK, 2015, 126 (05): : 545 - 550
  • [37] Belief Propagation Stereo Matching Compared to iSGM on Binocular or Trinocular Video Data
    Khan, Waqar
    Suaste, Veronica
    Caudillo, Diego
    Klette, Reinhard
    2013 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2013, : 791 - 796
  • [38] Accurate and Fast Convergent Initial-Value Belief Propagation for Stereo Matching
    Wang, Xiaofeng
    Liu, Yiguang
    PLOS ONE, 2015, 10 (09):
  • [39] Segment-based stereo matching using belief propagation and a self-adapting dissimilarity measure
    Klaus, Andreas
    Sormann, Mario
    Karner, Konrad
    18TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 3, PROCEEDINGS, 2006, : 15 - +
  • [40] DEPTH ESTIMATION IN LIGHT FIELD CAMERA ARRAYS BASED ON MULTI-STEREO MATCHING AND BELIEF PROPAGATION
    Rogge, Segolene
    Munteanu, Adrian
    2018 - 3DTV-CONFERENCE: THE TRUE VISION - CAPTURE, TRANSMISSION AND DISPLAY OF 3D VIDEO (3DTV-CON), 2018,
12345