The infection algorithm:: An artificial epidemic approach for dense stereo correspondence

被引:13
|
作者
Olague, Gustavo
Fernandez, Francisco
Perez, Cynthia B.
Lutton, Evelyne
机构
[1] Ctr Invest Cient & Educ Super Ensenada, CICESE Res Ctr, Div Appl Phys, Ensenada 22860, Baja California, Mexico
[2] Univ Extremadura, Dept Comp Sci, Ctr Univ Merida, Merida 06800, Spain
[3] CICESE Res Ctr, EvoVis Lab, Ensenada 22860, Baja California, Mexico
[4] INRIA Rocquencourt, Complex Team, F-78153 Le Chesnay, France
关键词
image matching; epipolar geometry; stereo vision; artificial epidemics; infection algorithm;
D O I
10.1162/artl.2006.12.4.593
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a new bio-inspired approach applied to a problem of stereo image matching. This approach is based on an artificial epidemic process, which we call the infection algorithm. The problem at hand is a basic one in computer vision for 3D scene reconstruction. It has many complex aspects and is known as an extremely difficult one. The aim is to match the contents of two images in order to obtain 3D information that allows the generation of simulated projections from a viewpoint that is different from the ones of the initial photographs. This process is known as view synthesis. The algorithm we propose exploits the image contents in order to produce only the necessary 3D depth information, while saving computational time. It is based on a set of distributed rules, which propagate Eke an artificial epidemic over the images. Experiments on a pair of real images are presented, and realistic reprojected images have been generated.
引用
收藏
页码:593 / 615
页数:23
相关论文
共 50 条
  • [1] The infection algorithm:: An artificial epidemic approach for dense stereo matching
    Olague, G
    de Vega, FF
    Pérez, CB
    Lutton, E
    [J]. PARALLEL PROBLEM SOLVING FROM NATURE - PPSN VIII, 2004, 3242 : 622 - 632
  • [2] An evolutionary infection algorithm for dense stereo correspondence
    Pérez, CB
    Olague, G
    Fernandez, F
    Lutton, E
    [J]. APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS, 2005, 3449 : 294 - 303
  • [3] An Improved Stereo Correspondence Algorithm of Dense Points
    Wang Rui
    Yang Runze
    Yin Xiaochun
    [J]. ISTM/2011: 9TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, 2011, : 69 - 72
  • [4] Dense Stereo Matching Based on Multiobjective Fitness Function-A Genetic Algorithm Optimization Approach for Stereo Correspondence
    Mahato, Manimala
    Gedam, Shirishkumar
    Joglekar, Jyoti
    Buddhiraju, Krishna Mohan
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2019, 57 (06): : 3341 - 3353
  • [5] An artificial life approach to dense stereo disparity
    Olague, Gustavo
    Perez, Cynthia B.
    Fernandez, Francisco
    Lutton, Evelyne
    [J]. ARTIFICIAL LIFE AND ROBOTICS, 2009, 13 (02) : 585 - 596
  • [6] A Dense Stereo Correspondence Algorithm for Hardware Implementation with Enhanced Disparity Selection
    Nalpantidis, Lazaros
    Sirakoulis, Georgios Ch
    Gasteratos, Antonios
    [J]. ARTIFICIAL INTELLIGENCE: THEORIES, MODELS AND APPLICATIONS, SETN 2008, 2008, 5138 : 365 - +
  • [7] Growing aggregation algorithm for dense two-frame stereo correspondence
    Binaghi, Elisabetta
    Gallo, Ignazio
    Fornasier, Chiara
    Raspanti, Mario
    [J]. VISAPP 2006: PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 2, 2006, : 326 - +
  • [8] Dense Features for Semi-Dense Stereo Correspondence
    Olga Veksler
    [J]. International Journal of Computer Vision, 2002, 47 : 247 - 260
  • [9] Weighted matchings for dense stereo correspondence
    Fielding, G
    Kam, M
    [J]. PATTERN RECOGNITION, 2000, 33 (09) : 1511 - 1524
  • [10] Semi-dense stereo correspondence with dense features
    Veksler, O
    [J]. 2001 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOL 2, PROCEEDINGS, 2001, : 490 - 497