Exploring the representation capabilities of the HOG descriptor

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2011, Pages 1410-1417

  Tatu, Aditya ^a   Lauze, Francois ^a   Nielsen, Mads ^a   Kimia, Benjamin ^b  

^a UNIVERSITY OF COPENHAGEN   (Denmark)

^b Brown University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CALTECH; DESCRIPTORS; IMAGE SHARING; OBJECT CATEGORIES; RANDOM IMAGE; RECOGNITION STRATEGIES; SAMPLING THEOREMS; SOURCE IMAGES; SPARSE SET; TARGET IMAGES; VERY LARGE DATABASE; VISUAL APPEARANCE;

EQUIVALENCE CLASSES; VISUALIZATION;

OBJECT RECOGNITION;

EID: 84856655917     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCVW.2011.6130416     Document Type: Conference Paper

References (21)

1. S. Belongie, J. Malik, and J. P. J. Shape matching and object recognition using shape contexts. IEEE TPAMI, 24:509-522, 2002.
2. I. Biederman. Recognition-by-components: a theory of human image understanding. Psychol. Rev, 94(2), Apr. 1987.
3. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In Proceedings of CVPR 2005, pages 886-893, 2005.
4. J.-P. Dedieu and D. Nowicki. Symplectic methods for the approximation of the exponential map and the newton iteration on riemannian submanifolds. Journal of Complexity, 21:487-501, 2005.
5. J. Deng, A. Berg, K. Li, and L. Fei-Fei. What does classifying more than 10, 000 images tell us? In ECCV 2010, pages 71-84, 2010.
6. J. Deng, W. Dong, R. Socher, L. J. Li, and L. Fei-Fei. ImageNet: A large scale hierarchical image database. In CVPR 2009, 2009.
7. L. C. Evans. Partial differential equations, volume 19 of Graduate Studies in Mathematics. American Mathematical Society, 1998.
8. P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan. Object Detection with Discriminatively Trained Part-Based Models. PAMI, 32(9):1627-1645, 2010.
9. M. Fink and S. Ullman. From Aardvark to Zorro: A Benchmark for Mamal Image Classification. IJCV, 77(1-3), May 2008.
10. W. T. Freeman and M. Roth. Orientation histograms for hand gesture recognition. In InternationalWorkshop on Automatic Face and Gesture Recognition, pages 296-301, 1995.
11. L. D. Griffin. Scale imprecision space. IMAVIS, 15:369-398, 1997.
12. C. Harris and M. Stephen. A Combined Corner and Edge Detector. In Proceedings of the 4th Alvey Vision Conference, pages 147-151, 1988.
13. Y. Ke and R. Sukthankar. Pca-sift: A more distinctive representation for local image descriptors. In Proceedings of CVPR 2004, pages 511-517, 2004.
14. J. J. Koenderink and A. J. van Doorn. The structure of locally orderless images. IJCV, 31(2/3):159-168, 1999.
15. M. Lillholm, M. Nielsen, and L. D. Griffin. Feature-based image analysis. IJCV, 52:73-95, 2003.
16. D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60:91-110, 2004.
17. D. G. Luenberger. Optimization by vector space methods. Wiley Professional Paperback. Wiley Interscience, 1969.
18. K. V. Mardia and P. E. Jupp. Directional statistics. Wiley, 2000.
19. K. Mikolajczyk and C. Schmid. A performance evaluation of local descriptors. IEEE TPAMI, 27:1615-1630, 2005.
20. B. C. Russell, A. Torralba, and K. Murphy. LabelMe: a database and web-based too for image annotation. AI Lab Memo AIM 2005-025. Technical report, MIT, 2005.
21. B. van Ginneken and B. tar Haar Romeny. Applications of locally orderless images. Journal iof Visual Communication and Image Representation, 11:196-208, 2000.