Submodular object recognition

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

Volumn , Issue , 2014, Pages 2457-2464

  Zhu, Fan ^a   Jiang, Zhuolin ^b   Shao, Ling ^a  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

^b HUAWEI NOAH S ARK LAB   (China)

Author keywords

CPMC; Object Recognition; Regression; Submodularity

Indexed keywords

IMAGE SEGMENTATION;

BENCHMARK DATASETS; BOTTOM-UP PROCESS; CATEGORY SPECIFICS; CPMC; FACILITY LOCATIONS; OBJECTIVE FUNCTIONS; REGRESSION; SUBMODULARITY;

OBJECT RECOGNITION;

EID: 84911445359     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.315     Document Type: Conference Paper

References (29)

1. Y. Bengio, P. Lamblin, D. Popovici, and H. Larochelle. Greedy layer-wise training of deep networks. In NIPS, 2007.
2. J. Carreira, F. Li, and C. Sminchisescu. Object recognition by sequential figure-ground ranking. International Journal of Computer Vision, 98(3):243-262, 2012.
3. J. Carreira and C. Sminchisescu. Constrained parametric min-cuts for automatic object segmentation. In CVPR, 2010.
4. Q. Chen, Z. Song, Y. Hua, Z. Huang, and S. Yan. Hierarchical matching with side information for image classification. In ICCV, 2012.
5. J. Dong, W. Xia, Q. Chen, J. Feng, Z. Huang, and S. Yan. Subcategory-aware object classification. In ICCV, 2013.
6. M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman. The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results. http://www.pascal-network.org/challenges/VOC/voc2007/workshop/index.html.
7. L. Fei-Fei, R. Fergus, and P. Perona. One-shot learning of object categories. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 28(4):594-611, 2006.
8. V. Ferrari, F. Jurie, and C. Schmid. From images to shape models for object detection. International Journal of Computer Vision, 87(3):284-303, 2010.
9. B. Fulkerson, A. Vedaldi, and S. Soatto. Class segmentation and object localization with superpixel neighborhoods. In ICCV, 2009.
10. R. D. Galvão. Uncapacitated facility location problems: contributions. Pesquisa Operacional, 24(1):7-38, 2004.
11. S. Gould, R. Fulton, and D. Koller. Decomposing a scene into geometric and semantically consistent regions. In ICCV, 2009.
12. H. Harzallah, F. Jurie, and C. Schmid. Combining efficient object localization and image classification. In ICCV, 2009.
13. X. He, R. S. Zemel, and M. A. Carreira-Perpinán. Multiscale conditional random fields for image labeling. In CVPR, 2004.
14. Z. Jiang and L. S. Davis. Submodular salient region detection. In CVPR, 2013.
15. Z. Jiang, Z. Lin, and L. Davis. Label consistent k-svd: Learning a discriminative dictionary for recognition. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 35(11):2651-2664, 2013.
16. L. Ladicky, C. Russell, P. Kohli, and P. H. Torr. Associative hierarchical crfs for object class image segmentation. In ICCV, 2009.
17. S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In CVPR, 2006.
18. N. Lazic, I. Givoni, B. Frey, and P. Aarabi. Floss: Facility location for subspace segmentation. In ICCV, 2009.
19. J. Leskovec, A. Krause, C. Guestrin, C. Faloutsos, J. VanBriesen, and N. Glance. Cost-effective outbreak detection in networks. In SIGKDD, 2007.
20. M.-Y. Liu, R. Chellappa, O. Tuzel, and S. Ramalingam. Entropy-rate clustering: Cluster analysis via maximizing a submodular function subject to a matroid constraint. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 36(1):99-112, 2013.
21. G. L. Nemhauser, L. A. Wolsey, and M. L. Fisher. An analysis of approximations for maximizing submodular set functionsi. Mathematical Programming, 14(1):265-294, 1978.
22. M.-E. Nilsback and A. Zisserman. A visual vocabulary for flower classification. In CVPR, 2006.
23. F. Perronnin, J. Sánchez, and T. Mensink. Improving the fisher kernel for large-scale image classification. In ECCV. 2010.
24. T. Quack, V. Ferrari, B. Leibe, and L. Van Gool. Efficient mining of frequent and distinctive feature configurations. In ICCV, 2007.
25. A. Rabinovich, S. Belongie, T. Lange, and J. M. Buhmann. Model order selection and cue combination for image segmentation. In CVPR, 2006.
26. A. Shaban, H. R. Rabiee, M. Farajtabar, and M. Ghazvininejad. From local similarity to global coding: An application to image classification. In CVPR, 2013.
27. J. Shi and J. Malik. Normalized cuts and image segmentation. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 22(8):888-905, 2000.
28. J. Shotton, J. Winn, C. Rother, and A. Criminisi. Textonboost for image understanding: Multi-class object recognition and segmentation by jointly modeling texture, layout, and context. International Journal of Computer Vision, 81(1):2-23, 2009.
29. J. Yang, K. Yu, Y. Gong, and T. Huang. Linear spatial pyramid matching using sparse coding for image classification. In CVPR, 2009.