Efficient object detection and segmentation for fine-grained recognition

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2013, Pages 811-818

  Angelova, Anelia ^a   Zhu, Shenghuo ^a  

^a NEC LABORATORIES AMERICA   (United States)

Author keywords

fine grained categorization; image segmentation; Laplacian propagation

Indexed keywords

BENCHMARK DATASETS; CLASSIFICATION ALGORITHM; DIFFERENT CLASS; EFFICIENT OBJECT DETECTIONS; FINE-GRAINED CATEGORIZATION; LAPLACIANS; SEGMENTATION ALGORITHMS; STATE-OF-THE-ART METHODS;

ALGORITHMS; BIRDS; IMAGE SEGMENTATION; PATTERN RECOGNITION;

CLASSIFICATION (OF INFORMATION);

EID: 84887340679     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2013.110     Document Type: Conference Paper

References (28)

1. B. Alexe, T. Deselaers, and V. Ferrari. Classcut for unsupervised class segmentation. ECCV, 2010.
2. S. Branson, C. Wah, B. Babenko, F. Schroff, P. Welinder, P. Perona, and S. Belongie. Visual recognition with humans in the loop. ECCV, 2010.
3. Y. Chai, V. Lempitsky, and A. Zisserman. Bicos: A bi-level co-segmentation method for image classification. ICCV, 2011.
4. G. Csurka and F. Perronnin. An efficient approach to semantic segmentation. IJCV, 2011.
5. Q. Dai and D. Hoiem. Learning to localize detected objects. CVPR, 2012.
6. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. CVPR, 2005.
7. R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin. Liblinear: A library for large linear classification. Journal of Machine Learning Research, 2008.
8. R. Farrell, O. Oza, N. Zhang, V. Morariu, T. Darrell, and L. Davis. Birdlets: Subordinate categorization using volumetric primitives and pose-normalized appearance. ICCV, 2011.
9. P. Felzenszwalb and D. Huttenlocher. Efficient graph-based image segmentation. IJCV, 2004.
10. C. Gu, J. Lim, P. Arbelaez, and J. Malik. Recognition using regions. CVPR, 2011.
11. D. Hoiem, A. Efros, and M. Hebert. Closing the loop on scene interpretation. CVPR, 2008.
12. S. Ito and S. Kubota. Object classfication using heterogeneous co-occurrence features. ECCV, 2010.
13. A. Joulin, F. Bach, and J. Ponce. Discriminative clustering for image co-segmentation. CVPR, 2010.
14. F. Khan, J. van de Weijer, and M. Vanrell. Top-down color attention for object recognition. ICCV, 2009.
15. N. Kumar, P. Belhumeur, A. Biswas, D. Jacobs, J. Kress, I. Lopez, and J. Soares. Leafsnap: A computer vision system for automatic plant species identification. ECCV, 2012.
16. Y. Lin, F. Lv, S. Zhu, M. Yang, T. Cour, K. Yu, L. Cao, and T. Huang. Large-scale image classification: fast feature extraction and svm training. CVPR, 2011.
17. M.-E. Nilsback and A. Zisserman. Automated flower classification over a large number of classes. ICVGIP, 2008.
18. M.-E. Nilsback and A. Zisserman. An automatic visual flora-segmentation and classification of flower images. DPhil Thesis, University of Oxford, UK, 2009.
19. O. Parkhi, A. Vedaldi, C. V. Jawahar, and A. Zisserman. The truth about cats and dogs. ICCV, 2011.
20. O. Parkhi, A. Vedaldi, C. V. Jawahar, and A. Zisserman. Cats and dogs. CVPR, 2012.
21. C. Rother, V. Kolmogorov, and A. Blake. Grabcut: Interactive foreground extraction using iterated graph cuts. ACM Trans. Graphics, 2004.
22. O. Russakovsky, Y. Lin, K. Yu, and L. Fei-Fei. Objectcentric spatial pooling for image classification. ECCV, 2012.
23. J. Sanchez, F. Perronnin, and T. de Campos. Modeling the spatial layout of images beyond spatial pyramids. Pattern Recognition Letters, 2012.
24. A. Vedaldi and B. Fulkerson. Vlfeat library.
25. J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Gong. Locality-constrained linear coding for image classification. CVPR, 2010.
26. P. Welinder, S. Branson, T. Mita, C. Wah, F. Schroff, S. Belongie, and P. Perona. Caltech-ucsd birds 200. Technical Report CNS-TR-2010-001, California Institute of Technology, 2010.
27. B. Yao, A. Khosla, and L. Fei-Fei. Combining randomization and discrimination for fine grained image categorization. CVPR, 2011.
28. D. Zhou, O. Bousquet, T. Lal, J. Weston, and B. Scholkopf. Learning with local and global consistency. NIPS, 2004.