Home   >   CSC-OpenAccess Library   >    Manuscript Information
Multiple Ant Colony Optimizations for Stereo Matching
Wangxiaonian, Ajay Somkuwar
Pages - 203 - 217     |    Revised - 30-10-2009     |    Published - 30-11-2009
Volume - 3   Issue - 5    |    Publication Date - November 2009  Table of Contents
MORE INFORMATION
KEYWORDS
Mammography, medical image processing, Adaptive Resonance theory, image enhancement
ABSTRACT
The stereo matching problem, which obtains the correspondence between right and left images, can be cast as a search problem. The matching of all candidates in the same line forms a 2D optimization task and the two dimensional (2D) optimization is a NP-hard problem. There are two characteristics in stereo matching. Firstly, the local optimization process along each scan-line can be done concurrently; secondly, there are some relationship among adjacent scan-lines can be explored to promote the matching correctness. Although there are many methods, such as GCPs, GGCPs are proposed, but these so called GCPs maybe not be ground. The relationship among adjacent scan-lines is posteriori, that is to say the relationship can only be discovered after every optimization is finished. The Multiple Ant Colony Optimization(MACO) is efficient to solve large scale problem. It is a proper way to settle down the stereo matching task with constructed MACO, in which the master layer values the sub-solutions and propagate the reliability after every local optimization is finished. Besides, whether the ordering and uniqueness constraints should be considered during the optimization is discussed, and the proposed algorithm is proved to guarantee its convergence to find the optimal matched pairs.
CITED BY (2)  
1 Mauricio, C. J. L., Edgar, F. S., & Samuel, R. H. E. (2012). Sistema Móvil de Virtualización, Edición y Visualización de Objetos 3D (VIAR).
2 Johari, H., Kaushik, V., & Upadhyay, P. K. (2010). Developing 3D Viewing Model from 2D Stereo Pair with its Occlusion Ratio. International Journal of Image Processing, 4(3), 251.
1 Google Scholar 
2 ScientificCommons 
3 Academic Index 
4 CiteSeerX 
5 refSeek 
6 iSEEK 
7 Socol@r  
8 ResearchGATE 
9 Bielefeld Academic Search Engine (BASE) 
10 OpenJ-Gate 
11 Scribd 
12 WorldCat 
13 SlideShare 
14 PDFCAST 
15 PdfSR 
A. F. Bobick and S. S. Intille. “Large occlusion stereo”. IJCV, 33(3):181–200, 1999.
A. L.Yuille and T. Poggio. ”Ageneralized ordering constraint for stereo correspondence”. A.I. Memo 777, AI Lab, MIT, 1984.
agents“. IEEE Transaction on Systems, Man& Cybernetics B, 1996,2692: 29-41. Cooperating Agents“, IEEE Transactions on Systems, Man, and Cybernetics–Part B, 26 (1): 29–41.
Babu Thomas, B. Yegnanarayana, S. Das: “Stereo-correspondence using Gabor logons and neural networks“. ICIP 1995: 2386-2389.
Brown MZ, Burschka D, Hager GD. ”Advances in Computational Stereo”. Transactions on Pattern Analysis and Machine Intelligence , August 2003, 25(8):993-1008.
Bullnheimer B, Kotsis G, Steauss C. “Parallelization strategies for the ant system. High Performance and Algorithms and Software in Nonlinear Optimization“, Applied Optimization, 1998,24:87-100
C. L. Zitnick and T. Kanade.”A cooperative algorithm for stereo matching and occlusion detection”. IEEE TPAMI, 22(7):675–684, 2000.
C. Lei, J. Selzer, and Y.H. Yang, ”Region-Tree based Stereo using Dynamic Programming Optimization”, Proc. IEEE Conf. on Computer Vision and Pattern Recognition, New York, NY: June 17-22, 2006, pp. 2378-2385.
C. Leung, B. Appleton and C. Sun, ”Fast stereo matching by iterated dynamic programming and quadtree subregioning”. British Machine Vision Conference vol. 1, Kingston University, London 2004: 97–106.
Chu SC, Roddick JF, Pan JS. ”Ant colony system with communication strategies”. Information Science, 2004,167:63-76.
D. Marr and T. Poggio, ”A Computational Theory of Human Stereo Vision”, Proc. Royal Soc. London B, vol. 204, pp. 301-328,1979.
Dorigo M, Manjezzo V, Colorni A. “The ant system: Optimization by a colony of cooperating agents“. IEEE Transaction on Systems, Man& Cybernetics B, 1996,2692: 29-41.
Ellabib I, Calamai P, Basir O. ”Exchange strategies for multiple Ant Colony System”. Information Sciences, 2007, 177(5): 1248-1264.
Gutjahr WJ. ”ACO Algorithms with Guaranteed Convergence to the Optional Solution”. Info.Processing Lett. 2002,82(3):145-153.
H. Baker and T. Binford. “Depth from edge and intensity based stereo”. In IJCAI81, pages 631–636, 1981.
Jun O, Yan GR. “A Multi-Group Ant Colony System”. International Conference on Machine Learning and Cybernetics.New York:IEEE Press,2004:117-121.
Kim J, Lee KM, Choi BT, et al. ”A dense stereo matching using two-pass dynamic programming with generalized ground control points”, IEEE CVPR, 2005,2:1075-1082.
Lorenzo Sorgi, Alessandro Neri: “Bidirectional Dynamic Programming for Stereo Matching“. ICIP 2006: 1013-1016.
M. Dorigo and C. Blum. ”Ant colony optimization theory: A survey”. Theoretical Computer Science, 344(2-3):243-278, 2005.
M. Gong and Y. H. Yang, “Multi-resolution stereo matching using genetic algorithm“, IEEE Workshop on Stereo and Multi-Baseline Vision, Dec. 2001.
M. Rahoual, R. Hadji and V. Bachelet, ”Parallel ant system for the set covering problem”.Third International Workshop on Ant Algorithms, Lecture Notes in Computer Science vol. 2463, Springer-Verlag, Heidelberg, Germany 2002: 262–267.
M. Randall, A. Lewis, ”A Parallel Implementation of Ant Colony Optimization”, Journal of Parallel and Distributed Computing, Volume 62, Number 9, 1421-1432, September 2002
Min Chul Sung, Sang Hwa Lee, Nam Ik Cho: “Stereo Matching using Multi-Directional Dynamic Programming and Edge Orientations“. ICIP (1) 2007: 233-236.
O. Veksler. “Efficient Graph-based Energy Minimization Methods in Computer Vision”. PhD thesis, Cornell University, 1999.
S. Birchfield and C. Tomasi. “Depth discontinuities by pixel-to-pixel stereo”. In ICCV, pages 1073–1080, 1998.
S. Roy and I. J. Cox. “A maximum-flow formulation of the N-camera stereo correspondence problem“. In ICCV, pages 492–499, 1998.
Scharstein D and Szeliski R. “A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms”, Int’l J. Computer Vision”, 2002,47(1):7-42,.
Stutzle T, Dorigo M. ”A short convergence proof for a class of ant colony optimization algorithm” , IEEE Transactions on evolutionary computation, 2002.6(4): 358-365.
Talbi EG, Roux O, Fonlupt C, et al. ”Parallel ant colonies for the quadratic assignment problem”. Future Generation Computer Systems, 2001,17:441-449.
Talbi EG, Roux O, Fonlupt C, et al. ”Parallel ant colonies for the quadratic assignment problem”. Future Generation Computer Systems, 2001,17:441-449.
Xiao-Nian Wang,Yuan-jing Feng,Zu-Ren Feng. ”Ant Colony Optimization for Image Segmentation”. Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005, 9(1):5355-5360.
Y. Boykov, O. Veksler, and R. Zabih. “Fast approximate energy minimization via graph cuts“. IEEE TPAMI, 23(11):1222–1239, 2001.
Y. Ohta and T. Kanade, ”Stereo by two-level dynamic programming”. IEEE TPAMI, 7(2):139–154, 1985.
Yip, Raymond K.K., Ho, W.P., ”A multi-level dynamic programming method for stereo line matching”, PRL(19), No. 9, 31 July 1998, pp. 839-855.
Associate Professor Wangxiaonian
- China
dawnyear@tongji.edu.cn
Dr. Ajay Somkuwar
Maulana Azad National Insititute of Technology - India