Integrating context and occlusion for car detection by hierarchical and-or model

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

Volumn 8694 LNCS, Issue PART 6, 2014, Pages 652-667

  Li, Bo ^a,b   Wu, Tianfu ^b   Zhu, Song Chun ^b  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

And Or Graph; Car Detection; Context; Occlusion

Indexed keywords

DEFORMATION; DYNAMIC PROGRAMMING; INFERENCE ENGINES;

AND-OR GRAPH; CAR DETECTION; CONTEXT; DEFORMABLE PART-BASED MODELS; DYNAMIC PROGRAMMING ALGORITHM; LEARNING PROCESS; METHOD OF LEARNING; OCCLUSION;

STATISTICAL TESTS;

EID: 84906345251     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-10599-4_42     Document Type: Conference Paper

References (32)

1. Azizpour, H., Laptev, I.: Object detection using strongly-supervised deformable part models. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part I. LNCS, vol.7572, pp. 836-849. Springer, Heidelberg (2012)
2. Behley, J., Steinhage, V., Cremers, A.: Laser-based Segment Classification Using a Mixture of Bag-of-Words. In: IROS (2013)
3. Branson, S., Perona, P., Belongie, S.: Strong supervision from weak annotation: Interactive training of deformable part models. In: ICCV (2011)
4. Chen, G., Ding, Y., Xiao, J., Han, T.X.: Detection evolution with multi-order contextual co-occurrence. In: CVPR (2013)
5. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: CVPR (2005)
6. Desai, C., Ramanan, D., Fowlkes, C.: Discriminative models for multi-class object layout. IJCV 95(1), 1-12 (2011)
7. Everingham, M., Van Gool, L., Williams, C., Winn, J., Zisserman, A.: The pascal visual object classes (voc) challenge. IJCV (2010)
8. Felzenszwalb, P., Girshick, R., McAllester, D., Ramanan, D.: Object detection with discriminatively trained part-based models. TPAMI (2010)
9. Felzenszwalb, P., McAllester, D.: Object detection grammars. Tech. rep., University of Chicago, Computer Science TR-2010-02 (2010)
10. Felzenszwalb, P., Huttenlocher, D.: Distance transforms of sampled functions. Theory of Computing (2012)
11. Geiger, A., Lenz, P., Urtasun, R.: Are we ready for autonomous driving? the kitti vision benchmark suite. In: CVPR (2012)
12. Geiger, A.,Wojek, C., Urtasun, R.: Joint 3D estimation of objects and scene layout. In: NIPS (2011)
13. Girshick, R., Felzenszwalb, P., McAllester, D.: Object detection with grammar models. In: NIPS (2011)
14. Girshick, R.B., Felzenszwalb, P.F., McAllester, D.: Discriminatively trained deformable part models, release 5, http://people.cs.uchicago.edu/~rbg/ latent-release5/
15. Hejrati, M., Ramanan, D.: Analyzing 3D objects in cluttered images. In: NIPS (2012)
16. Hoiem, D., Chodpathumwan, Y., Dai, Q.: Diagnosing error in object detectors. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part III. LNCS, vol.7574, pp. 340-353. Springer, Heidelberg (2012)
17. Hoiem, D., Efros, A., Hebert, M.: Putting objects in perspective. IJCV 80(1), 3-15 (2008)
18. Hu, W., Zhu, S.C.: Learning 3D object templates by quantizing geometry and appearance spaces. TPAMI (to appear, 2014)
19. Li, B., Hu, W., Wu, T.F., Zhu, S.C.: Modeling occlusion by discriminative and-or structures. In: ICCV (2013)
20. Li, B., Song, X., Wu, T.F., Hu, W., Pei, M.: Coupling-and-decoupling: A hierarchical model for occlusion-free object detection. PR 47, 3254-3264 (2014)
21. Mathias, M., Benenson, R., Timofte, R., Van Gool, L.: Handling occlusions with franken-classifiers. In: ICCV (2013)
22. McAllester, D., Keshet, J.: Generalization bounds and consistency for latent structural probit and ramp loss. In: NIPS (2011)
23. Ouyang, W., Wang, X.: Single-pedestrian detection aided by multi-pedestrian detection. In: CVPR (2013)
24. Pepik, B., Stark, M., Gehler, P., Schiele, B.: Teaching 3d geometry to deformable part models. In: CVPR (2012)
25. Pepik, B., Stark, M., Gehler, P., Schiele, B.: Occlusion patterns for object class detection. In: CVPR (2013)
26. Sadeghi, M., Farhadi, A.: Recognition using visual phrases. In: CVPR (2011)
27. Song, X., Wu, T.F., Jia, Y., Zhu, S.C.: Discriminatively trained and-or tree models for object detection. In: CVPR (2013)
28. Tang, S., Andriluka, M., Schiele, B.: Detection and tracking of occluded people. In: BMVC (2012)
29. Tu, Z., Bai, X.: Auto-context and its application to high-level vision tasks and 3D brain image segmentation. TPAMI (2010)
30. Yang, Y., Baker, S., Kannan, A., Ramanan, D.: Recognizing proxemics in personal photos. In: CVPR (2012)
31. Zhu, L., Chen, Y., Yuille, A., Freeman, W.: Latent hierarchical structural learning for object detection. In: CVPR (2010)
32. Zhu, S.C., Mumford, D.: A stochastic grammar of images. Found. Trends. Comput. Graph. Vis. (2006)