An integer projected fixed point method for graph matching and MAP inference

Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference

Volumn , Issue , 2009, Pages 1114-1122

  Leordeanu, Marius ^a   Hebert, Martial ^a   Sukthankar, Rahul ^b  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b INTEL CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BELIEF PROPAGATION; COMPUTER VISION; INFERENCE ENGINES; LEARNING SYSTEMS; PATTERN MATCHING; PROBLEM SOLVING;

CONVERGENCE PROPERTIES; ESSENTIAL PROBLEMS; FIXED-POINTS METHOD; GRAPH MATCHINGS; GRAPH-MATCHING ALGORITHMS; ITERATED CONDITIONAL MODES; MACHINE-LEARNING; MAP INFERENCES; PERFORMANCE; VISION LEARNING;

QUADRATIC PROGRAMMING;

EID: 84858731529     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (17)

1. A. Berg, T. Berg and J. Malik. Shape matching and object recognition using low distortion correspondences. Computer Vision and Pattern Recognition, 2005
2. R. Zass and A. Shashua. Probabilistic Graph and Hypergraph Matching. Computer Vision and Pattern Recognition, 2008
3. T. Cour, P. Srinivasan and J. Shi. Balanced Graph Matching. Neural Information Processing Systems, 2006
4. S. Gold, and A. Rangarajan. A graduated assignment algorithm for graph matching. Pattern Analysis and Machine Intelligence, 1996
5. M. Leordeanu and M. Hebert. A Spectral Technique for Correspondence Problems using Pairwise Constraints. International Conference on Computer Vision, 2005
6. M. Leordeanu and M. Hebert. Unsupervised Learning for Graph Matching. Computer Vision and Pattern Recognition, 2009
7. C. Schellewald and C. Schnorr. Probabilistic subgraph matching based on convex relaxation. EMMCVPR, 2005
8. P.H.S Torr. Solving markov random fields using semi definite programming. Artificial Intelligence and Statistics, 2003
9. B. Rainer, M. Dell'Amico and S. Martello. Assignment Problems. SIAM Publications, 2009
10. J. Besag. On the Statistical Analysis of Dirty Pictures. JRSS, 1986
11. T. Cour and J. Shi. Solving Markov Random Fields with Spectral Relaxation. International Conference on Artificial Intelligence and Statistics, 2007
12. M. Leordeanu and M. Hebert. Efficient MAP approximation for dense energy functions. International Conference on Machine Learning, 2006
13. P. Ravikumar and J. Lafferty. Quadratic Programming Relaxations for Metric Labeling and Markov Random Field MAP Estimation, International Conference on Machine Learning, 2006
14. M. Frank and P. Wolfe. An algorithm for quadratic programming, Naval Research Logistics Quarterly, 1956.
15. N.W. Brixius and K.M. Anstreicher. Solving quadratic assignment problems using convex quadratic programming relaxations, Optimization Methods and Software, 2001
16. J. Maciel and J.P. Costeira. A global solution to sparse correspondence problems Pattern Analysis and Machine Intelligence, 2003
17. L. Torresani, V. Kolmogorov and C. Rother. Feature correspondence via graph matching: Models and global optimization. European Conference on Computer Vision, 2008