The fastest deformable part model for object detection

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

Volumn , Issue , 2014, Pages 2497-2504

  Yan, Junjie ^a   Lei, Zhen ^a   Wen, Longyin ^a   Li, Stan Z ^a  

^a INSTITUTE OF AUTOMATION   (China)

Author keywords

deformable part model; face detection; object detection

Indexed keywords

EXTRACTION; FACE RECOGNITION; FEATURE EXTRACTION; LEARNING TO RANK; OBJECT DETECTION; TABLE LOOKUP;

2D CORRELATION; DEFORMABLE PART MODELS; FIRST-ORDER APPROXIMATIONS; GRADIENT ALGORITHM; LINEAR COMBINATIONS; LOOK UP TABLE; MATRIX INDICES; STATE OF THE ART;

OBJECT RECOGNITION;

EID: 84911377093     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.320     Document Type: Conference Paper

References (36)

1. J.-F. Cai, E. J. Candès, and Z. Shen. A singular value thresholding algorithm for matrix completion. SIAM Journal on Optimization, 2010.
2. E. J. Candès, X. Li, Y. Ma, and J. Wright. Robust principal component analysis? Journal of the ACM (JACM), 2011.
3. T. Dean, M. A. Ruzon, M. Segal, J. Shlens, S. Vijayanarasimhan, and J. Yagnik. Fast, accurate detection of 100, 000 object classes on a single machine. In CVPR, 2013.
4. P. Dollár, R. Appel, S. Belongie, and P. Perona. Fast feature pyramids for object detection. PAMI, 2014.
5. P. Dollár, R. Appel, and W. Kienzle. Crosstalk cascades for framerate pedestrian detection. In ECCV. Springer, 2012.
6. P. Dollár, S. Belongie, and P. Perona. The fastest pedestrian detector in the west. BMVC 2010, 2010.
7. P. Dollár, C. Wojek, B. Schiele, and P. Perona. Pedestrian detection: An evaluation of the state of the art. PAMI, 34, 2012.
8. C. Dubout and F. Fleuret. Exact acceleration of linear object detectors. In ECCV. Springer, 2012.
9. M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zis-serman. The pascal visual object classes (voc) challenge. IJCV, 2010.
10. P. Felzenszwalb, R. Girshick, and D. McAllester. Cascade object detection with deformable part models. In CVPR. IEEE, 2010.
11. P. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained part-based models. PAMI, 2010.
12. P. F. Felzenszwalb, R. B. Girshick, and D. McAllester. Dis-criminatively trained deformable part models, release 4. http://people.cs.uchicago.edu/pff/latent-release4/.
13. W. T. Freeman and E. H. Adelson. The design and use of steerable filters. TPAMI, 1991.
14. R. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In CVPR, 2014.
15. R. B. Girshick, H. O. Song, and T. Darrell. Discriminatively activated sparselets. In ICML, 2013.
16. I. Kokkinos. Rapid deformable object detection using dual-tree branch-and-bound. In NIPS, 2011.
17. I. Kokkinos. Shufflets: Shared mid-level parts for fast object detection. In ICCV. IEEE, 2013.
18. M. Kostinger, P. Wohlhart, P. Roth, and H. Bischof. Annotated facial landmarks in the wild: A large-scale, real-world database for facial landmark localization. In ICCV Workshops. IEEE, 2011.
19. A. Krizhevsky, I. Sutskever, and G. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 2012.
20. C. H. Lampert, M. B. Blaschko, and T. Hofmann. Efficient subwindow search: A branch and bound framework for object localization. PAMI, 2009.
21. R. Manduchi, P. Perona, and D. Shy. Efficient deformable filter banks. TSP, 1998.
22. M. Pedersoli, A. Vedaldi, and J. Gonzalez. A coarse-to-fine approach for fast deformable object detection. In CVPR. IEEE, 2011.
23. H. Pirsiavash and D. Ramanan. Steerable part models. In CVPR. IEEE, 2012.
24. V. Prisacariu and I. Reid. fasthog-a real-time gpu implementation of hog. Technical report, Oxford University, 2009.
25. R. Rigamonti, V. Lepetit, and P. Fua. Learning separable filters. In CVPR. IEEE, 2012.
26. X. Shen, Z. Lin, J. Brandt, and W. Ying. Detecting and aligning faces by image retrieval. In CVPR. IEEE, 2013.
27. H. O. Song, S. Zickler, T. Althoff, R. Girshick, M. Fritz, C. Geyer, P. Felzenszwalb, and T. Darrell. Sparselet models for efficient multiclass object detection. In ECCV. Springer, 2012.
28. P. Sudowe and B. Leibe. Efficient Use of Geometric Constraints for Sliding-Window Object Detection in Video. In ICVS'11, 2011.
29. K.-C. Toh and S. Yun. An accelerated proximal gradient algorithm for nuclear norm regularized linear least squares problems. Pacific Journal of Optimization, 2010.
30. P. Viola and M. Jones. Robust real-time face detection. IJCV, 2004.
31. L. Wolf, H. Jhuang, and T. Hazan. Modeling appearances with low-rank svm. In CVPR. IEEE, 2007.
32. J. Yan, Z. Lei, D. Yi, and S. Z. Li. Multi-pedestrian detection in crowded scenes: A global view. In CVPR. IEEE, 2012.
33. J. Yan, X. Zhang, Z. Lei, S. Liao, and S. Z. Li. Robust multiresolution pedestrian detection in traffic scenes. In CVPR. IEEE, 2013.
34. J. Yan, X. Zhang, Z. Lei, D. Yi, and S. Z. Li. Structural models for face detection. In FG. IEEE, 2013.
35. Y. Yang and D. Ramanan. Articulated pose estimation with flexible mixtures-of-parts. In CVPR. IEEE, 2011.
36. X. Zhu and D. Ramanan. Face detection, pose estimation, and landmark localization in the wild. In CVPR. IEEE, 2012.