Learning a fast emulator of a binary decision process

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4844 LNCS, Issue PART 2, 2007, Pages 236-245

  Šochman, Jan ^a   Matas, Jiří ^a  

^a CZECH TECHNICAL UNIVERSITY IN PRAGUE   (Czech Republic)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTER VISION; LEARNING SYSTEMS;

BINARY DECISION TASK; DECISION TIME; FAST EMULATOR; KADIR-BRADY DETECTOR; POINT DETECTORS;

DECISION THEORY;

EID: 38149088282     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-76390-1_24     Document Type: Conference Paper

References (15)

1. Šochman, J., Matas, J.: WaldBoost - learning for time constrained sequential detection. In: CVPR, Los Alamitos, USA, vol. 2, pp. 150-157 (2005)
2. Mikolajczyk, K., Schmid, C.: Scale and affine invariant interest point detectors. IJCV 60(1), 63-86 (2004)
3. Kadir, T., Brady, M.: Saliency, scale and image description. IJCV 45(2) (2001)
4. Grabner, M., Grabner, H., Bischof, H.: Fast approximated SIFT. In: ACCV, pp. I:918-927 (2006)
5. Bay, H., Tuytelaars, T., Van Gool, L.: SURF: Speeded up robust features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, Springer, Heidelberg (2006)
6. Viola, P., Jones, M.: Robust real time object detection. In: SCTV, Vancouver, Canada (2001)
7. Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., Van Gool, L.: A comparison of affine region detectors. In: IJCV (2005)
8. Lepetit, V., Lagger, P., Fua, P.: Randomized trees for real-time keypoint recognition. In: CVPR, vol. II, pp. 775-781 (2005)
9. Rosten, E., Drummond, T.: Machine learning for high-speed corner detection. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 430-443. Springer, Heidelberg (2006)
10. Martin, D., Fowlkes, C., Malik, J.: Learning to detect natural image boundaries using local brightness, color, and texture cues. PAMI 26(5), 530-549 (2004)
11. Schapire, R.E., Singer, Y.: Improved boosting algorithms using confidence-rated predictions. Machine Learning 37(3), 297-336 (1999)
12. Wald, A.: Sequential analysis. Dover, New York (1947)
13. Lienhart, R., Maydt, J.: An extended set of haar-like features for rapid object detection. In: ICIP (2002)
14. Fergus, R., Perona, P., Zisserman, A.: A sparse object category model for efficient learning and exhaustive recognition. In: CVPR, vol. 1, pp. 380-387 (2005)
15. Mikolajczyk, K.: Detection of local features invariant to affines transformations. PhD thesis, INPG, Grenoble (2002)