Are cars just 3D boxes? Jointly estimating the 3D shape of multiple objects

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

Volumn , Issue , 2014, Pages 3678-3685

  Zia, Muhammad Zeeshan ^a,c   Stark, Michael ^b   Schindler, Konrad ^a  

^a ETH ZURICH   (Switzerland)

^b STANFORD UNIVERSITY   (United States)

^c IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

3D object recognition; Scene understanding

Indexed keywords

OBJECT RECOGNITION;

3-D SCENE REPRESENTATION; 3D OBJECT RECOGNITION; GROUND PLANE CONTACT; MULTIPLE OBJECTS; OBJECT INTERACTIONS; OCCLUSION REASONING; SCENE UNDERSTANDING; WIREFRAME MODEL;

3D MODELING;

EID: 84911441879     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.470     Document Type: Conference Paper

References (40)

1. M. Andriluka, S. Roth, and B. Schiele. Pictorial structures revisited: People detection and articulated pose estimation. CVPR 2009.
2. A. Pentland. Perceptual organization and representation of natural form. AI'86.
3. S. Y. Bao and S. Savarese. Semantic structure from motion. CVPR11.
4. S. Y. Bao, Y Xiang, and S. Savarese. Object co-detection. ECCV2012.
5. L. Bourdev and J. Malik. Poselets: Body part detectors trained using 3d human pose annotations. ICCV2009.
6. R. A. Brooks. Symbolic reasoning among 3-d models and 2-d images. AI'81.
7. W. Choi, Y W. Chao, C. Pantofaru, and S. Savarese. Understanding indoor scenes using 3d geometric phrases. In CVPR 2013.
8. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. CVPR 2005.
9. L. Del Pero, J. Bowdish, B. Kermgard, E. Hartley, and K. Barnard. Understanding Bayesian rooms using composite 3d object models. CVPR 2013.
10. A. Ess, B. Leibe, K. Schindler, and L. V. Gool. Robust multi-person tracking from a mobile platform. PAMI, 31(10):1831-1846, 2009.
11. M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman. The pascal visual object classes (VOC) challenge. IJCV, 88(2):303-338, 2010.
12. P. F. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained part based models. PAMI, 32(9), 2010.
13. S. Fidler, S. Dickinson, and R. Urtasun. 3d object detection and viewpoint estimation with a deformable 3d cuboid model. NIPS 2012.
14. T. Gao, B. Packer, and D. Koller. A segmentation-aware object detection model with occlusion handling. CVPR 2011.
15. A. Geiger, P. Lenz, and R. Urtasun. Are we ready for autonomous driving? The KITTI vision benchmark suite. CVPR 2012.
16. A. Geiger, C. Wojek, and R. Urtasun. Joint 3d estimation of objects and scene layout. In NIPS 2011.
17. R. B. Girshick, P. F. Felzenszwalb, and D. McAllester. Object detection with grammar models. NIPS 2011.
18. A. Gupta, A. A. Efros, and M. Hebert. Blocks world revisited: Image understanding using qualitative geometry and mechanics. ECCV 2010.
19. V. Hedau, D. Hoiem, and D. Forsyth. Thinking inside the box: Using appearance models and context based on room geometry. ECCV 2010.
20. D. Hoiem, A. Efros, and M. Hebert. Putting objects in perspective. IJCV, 80(1):3-15, 2008.
21. E. Hsiao and M. Hebert. Occlusion reasoning for object detection under arbitrary viewpoint. CVPR 2012.
22. M. Isard and A. Blake. CONDENSATION-conditional density propagation for visual tracking. IJCV, 1(29), 1998.
23. S. Kwak, W. Nam, B. Han, and J. H. Han. Learning occlusion with likelihoods for visual tracking. ICCV 2011.
24. M. Leordeanu and M. Hebert. Smoothing-based optimization. CVPR 2008.
25. D. Lowe. Three-dimensional object recognition from single two-dimensional images. Artificial Intelligence, 31(3), 1987.
26. D. Marr and H. K. Nishihara. Representation and recognition of the spatial organization of three-dimensional shapes. PRSL B, 200:269-294, 1978.
27. D. Meger, C. Wojek, B. Schiele, and J. Little. Explicit occlusion reasoning for 3d object detection. BMVC 2011.
28. M. Hejrati and D. Ramanan. Analyzing 3d objects in cluttered images. NIPS12.
29. B. Pepik, P. Gehler, M. Stark, and B. Schiele. 3DDPM-3d deformable part models. ECCV 2012.
30. B. Pepik, M. Stark, P. Gehler, and B. Schiele. Occlusion patterns for object class detection. In CVPR 2013.
31. N. Silberman, D. Hoiem, P. Kohli, and R. Fergus. Indoor segmentation and support inference from RGBD images. ECCV 2012.
32. M. Stark, J. Krause, B. Pepik, D. Meger, J. Little, B. Schiele, and D. Koller. Fine-grained categorization for 3d scene understanding. In BMVC 2012.
33. A. Vedaldi and A. Zisserman. Structured output regression for detection with partial truncation. NIPS 2009.
34. H. Wang, S. Gould, and D. Koller. Discriminative learning with latent variables for cluttered indoor scene understanding. ECCV 2010.
35. X. Wang, T. Han, and S. Yan. An HOG-LBP human detector with partial occlusion handling. ICCV 2009.
36. C. Wojek, S. Walk, S. Roth, K. Schindler, and B. Schiele. Monocular visual scene understanding: understanding multi-object traffic scenes. PAMI, 2013.
37. Y. Xiang and S. Savarese. Estimating the aspect layout of object categories. CVPR 2012.
38. Y. Zhao and S.-C. Zhu. Scene parsing by integrating function, geometry and appearance models. In CVPR 2013.
39. M. Z. Zia, M. Stark, B. Schiele, and K. Schindler. Detailed 3d representations for object recognition and modeling. PAMI, 35(11):2608-2623, 2013.
40. M. Z. Zia, M. Stark, and K. Schindler. Explicit occlusion modeling for 3d object class representations. In CVPR 2013.