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[Special Effects立体视觉的实例源码

Description: Kolmogorov将graph cut应用于立体视觉的实例源码match-v3.1
Platform: | Size: 1259520 | Author: lcg2618@163.com | Hits:

[Special EffectsGraphCut

Description: 对Vladimir Kolmogorov,Yuri Boykov大牛的算法杰作——Graph Cut进行使用演示,代码力求精简,可供Graph Cut初学者参考学习。已通过VS2005编译。-Of Vladimir Kolmogorov, Yuri Boykov big cow masterpiece algorithm- Graph Cut for the use of demonstration, the code to be simple, for beginners Reference Graph Cut Study. VS2005 compiler has passed.
Platform: | Size: 17408 | Author: 杨金名 | Hits:

[Special Effectsmaxflow-v3.01.src.tar

Description: 基于文献“计算机视觉中的能量函数最小化的最小割/最大流”的最大流算法实现-An implementation of the maxflow algorithm described in An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Computer Vision. Yuri Boykov and Vladimir Kolmogorov. In IEEE Transactions on Pattern Analysis and Machine Intelligence, September 2004.
Platform: | Size: 13312 | Author: illusionme | Hits:

[Special EffectsMRF1.6

Description: This directory contains the MRF energy minimization software accompanying the paper [1] A Comparative Study of Energy Minimization Methods for Markov Random Fields. R. Szeliski, R. Zabih, D. Scharstein, O. Veksler, V. Kolmogorov, A. Agarwala, M. Tappen, and C. Rother. In Ninth European Conference on Computer Vision (ECCV 2006), volume 2, pages 16-29, Graz, Austria, May 2006. Optimization methods included: 1) ICM 2) Graph Cuts 3) Max-Product Belief Propagation The TRW / TRW-S method is currently not included, but hopefully will be in a future version. Instructions for compiling and using the software are included below. CREDITS: * MRF code, graph cut interface, and example code by Olga Veksler * Graph cut library by Yuri Boykov and Vladimir Kolmogorov * Belief propagation code by Marshall Tappen-This directory contains the MRF energy minimization software accompanying the paper [1] A Comparative Study of Energy Minimization Methods for Markov Random Fields. R. Szeliski, R. Zabih, D. Scharstein, O. Veksler, V. Kolmogorov, A. Agarwala, M. Tappen, and C. Rother. In Ninth European Conference on Computer Vision (ECCV 2006), volume 2, pages 16-29, Graz, Austria, May 2006. Optimization methods included: 1) ICM 2) Graph Cuts 3) Max-Product Belief Propagation The TRW/TRW-S method is currently not included, but hopefully will be in a future version. Instructions for compiling and using the software are included below. CREDITS: * MRF code, graph cut interface, and example code by Olga Veksler * Graph cut library by Yuri Boykov and Vladimir Kolmogorov * Belief propagation code by Marshall Tappen
Platform: | Size: 47104 | Author: fant | Hits:

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