Shape-from-recognition: Recognition enables meta-data transfer

Computer Vision and Image Understanding

Volumn 113, Issue 12, 2009, Pages 1222-1234

  Thomas, Alexander ^a   Ferrari, Vittorio ^b   Leibe, Bastian ^c   Tuytelaars, Tinne ^a   Gool, Luc Van ^a,b  

^a ESAT   (Belgium)

^b ETH ZURICH   (Switzerland)

^c RWTH AACHEN UNIVERSITY   (Germany)

Author keywords

Computer vision; Object recognition; Shape from X

Indexed keywords

2D IMAGES; 3-D SHAPE; COGNITIVE FEEDBACK; DEPTH MAP; HIGHER-LEVEL INFORMATION; INTERNATIONAL JOURNALS; LOW-LEVEL CUES; ROBUST OBJECT DETECTION; SHAPE MODEL; SHAPE-FROM-X; SURFACE NORMALS; TEST IMAGES; TRAINING IMAGE; VECTOR VALUED;

COMPUTER VISION; DATA TRANSFER; THREE DIMENSIONAL; TWO DIMENSIONAL;

OBJECT RECOGNITION;

EID: 70349987894     PISSN: 10773142     EISSN: 1090235X     Source Type: Journal    
DOI: 10.1016/j.cviu.2009.03.010     Document Type: Article

References (30)

1. Leibe B., Leonardis A., and Schiele B. Robust object detection with interleaved categorization and segmentation. International Journal of Computer Vision 77 1-3 (2008) 259-289
2. K. Rockland, G.V. Hoesen, Direct temporal-occipital feedback connections to striate cortex (V1) in the macaque monkey, in: Cereb. Cortex, Vol. 4, 1994, pp. 300-313.
3. Mumford D. Neuronal architectures for pattern-theoretic problems. Large-Scale Neuronal Theories of the Brain (1994) 125-152
4. Hoiem D., Efros A., and Hebert M. Putting objects in perspective. CVPR (2006) 2137-2144
5. Leibe B., Cornelis N., Cornelis K., and Van Gool L. Dynamici 3D scene analysis from a moving vehicle. CVPR (2007) 1-8
6. Biederman I. Recognition-by-components: a theory of human image understanding. Psychological Review 94 2 (1987) 115-147
7. Bergevin R., and Levine M.D. Generic object recognition: Building and matching coarse descriptions from line drawings. PAMI 15 1 (1993) 19-36
8. Hoiem D., Efros A.A., and Hebert M. Geometric context from a single image. ICCV (2005) 654-661
9. Sudderth E., Torralba A., Freeman W., and Willsky A. Depth from familiar objects: a hierarchical model for 3D scenes. CVPR 2 (2006) 2410-2417
10. Saxena A., Schulte J., and Ng A.Y. Learning depth from single monocular images. NIPS 18 (2005) 1-8
11. F. Han, S.-C. Zhu, Bayesian reconstruction of 3D shapes and scenes from a single image, Workshop Higher-Level Knowledge in 3D Modeling Motion Analysis (2003) 12-20.
12. T. Hassner, R. Basri, Example based 3D reconstruction from single 2d images, in: Beyond Patches Workshop at IEEE CVPR06, 2006, p. 15.
13. A. Hertzmann, C. Jacobs, N. Oliver, B. Curless, D. Salesin, Image analogies, SIGGRAPH Conference Proceedings (2001) 327-340.
14. Cheng L., Vishwanathan S.V.N., and Zhang X. Consistent image analogies using semi-supervised learning. CVPR (2008) 1-8
15. M. Kumar, P. Torr, A. Zisserman, OBJ CUT, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2005.
16. J. Winn, N. Jojic, LOCUS: Learning object classes with unsupervised segmentation, in: Proc. IEEE Intl. Conf. on Computer Vision (ICCV), Vol. 1, 2005, pp. 756-763.
17. H. Arora, N. Loeff, D.A. Forsyth, Unsupervised segmentation of objects using efficient learning, in: IEEE Conference on Computer Vision and Pattern Recognition, 2007.
18. Thomas A., Ferrari V., Leibe B., Tuytelaars T., Schiele B., and Van Gool L. Towards multi-view object class detection. CVPR 2 (2006) 1589-1596
19. Hoiem D., Rother C., and Winn J. 3D LayoutCRF for multi-view object class recognition and segmentation. CVPR (2007) 1-8
20. Kushal A., Schmid C., and Ponce J. Flexible object models for category-level 3D object recognition. CVPR (2007) 1-8
21. S. Savarese, L. Fei-Fei, 3d generic object categorization, localization and pose estimation, in: ICCV, 2007, pp. 1-8.
22. Cheng Y. Mean shift, mode seeking, and clustering. IEEE Trans. Pattern Anal. Mach. Intell. (1995) 790-799
23. Leibe B., and Schiele B. Interleaved object categorization and segmentation. BMVC (2003) 759-768
24. Lowe D.G. Distinctive image features from scale-invariant keypoints. IJCV 60 2 (2004) 91-110
25. H. Bay, T. Tuytelaars, L. Van Gool, SURF: Speeded up robust features, Proceedings ECCV, Springer LNCS 3951 (1) (2006) 404-417.
26. B. Russell, A. Torralba, K. Murphy, W. Freeman, LabelMe: a database and web-based tool for image annotation, MIT AI Lab Memo AIM-2005-025.
27. Mikolajczyk K., and Schmid C. Scale & affine invariant interest point detectors. IJCV 60 1 (2004) 63-86
28. S. Belongie, J. Malik, J. Puzicha, Shape context: A new descriptor for shape matching and object recognition, in: NIPS, 2000, pp. 831-837.
29. E. Seemann, B. Leibe, K. Mikolajczyk, B. Schiele, An evaluation of local shape-based features for pedestrian detection, in: Proceedings of the 16th British Machine Vision Conference, Oxford, UK, 2005, pp. 11-20.
30. Saxena A., Driemeyer J., Kearns J., and Ng A.Y. Robotic grasping of novel objects. NIPS 19 (2006) 1209-1216