Going into depth: Evaluating 2D and 3D cues for object classification on a new large-scale object dataset

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2011, Pages 1189-1196

  Browatzki, Björn ^a   Fischer, Jan ^b   Graf, Birgit ^b   Bulthoff, Heinrich H ^a   Wallraven, Christian ^c  

^a MAX PLANCK INSTITUTE FOR BIOLOGICAL CYBERNETICS   (Germany)

^b FRAUNHOFER INSTITUTE FOR MANUFACTURING ENGINEERING AND AUTOMATION IPA   (Germany)

^c Korea University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL EXPERIMENT; DATA SETS; NEW APPLICATIONS; OBJECT CATEGORIZATION; OBJECT CLASSIFICATION; RANGE DATA; RANGE SENSORS; SENSOR TECHNOLOGIES; SHAPE PROCESSING; THREE-DIMENSIONAL INFORMATION;

CLASSIFICATION (OF INFORMATION); IMAGE PROCESSING; SENSORS;

THREE DIMENSIONAL;

EID: 84856641335     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCVW.2011.6130385     Document Type: Conference Paper

References (23)

1. H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool. Speeded-up robust features (SURF). CVIU, 110(3):346-359, 2008.
2. O. Boiman, E. Shechtman, and M. Irani. In defense of nearest-neighbor based image classification. In CVPR, pages 1-8. IEEE, 2008.
3. A. Bosch, A. Zisserman, and X. Munoz. Representing shape with a spatial pyramid kernel. In CIVR, pages 401-408. ACM, 2007.
4. B. Bustos, D. Keim, D. Saupe, T. Schreck, and D. Vraníc. An experimental effectiveness comparison of methods for 3D similarity search. IJDL, 6(1):39-54, Feb. 2006.
5. R. Campbell. A Survey Of Free-Form Object Representation and Recognition Techniques. CVIU, 81(2):166-210, Feb. 2001.
6. M. Everingham, L. Gool, C. K. I. Williams, J. Winn, and A. Zisserman. The Pascal Visual Object Classes (VOC) Challenge. IJCV, 88(2):303-338, Sept. 2009.
7. L. Fei-Fei, R. Fergus, and P. Perona. Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories. CVIU, 106(1):59-70, Apr. 2007.
8. V. Ferrari, T. Tuytelaars, and L. Van Gool. Object detection by contour segment networks. ECCV, 3953(section 4):14-28, 2006.
9. T. Funkhouser, P. Min, M. Kazhdan, J. Chen, A. Halderman, D. Dobkin, and D. Jacobs. A search engine for 3D models. ACM Transactions on Graphics, 22(1):83-105, Jan. 2003.
10. G. Griffin, A. Holub, and P. Perona. Caltech-256 object category dataset. Mar. 2007.
11. M. Heczko, D. Keim, and D. Saupe. Methods for similarity search on 3D databases. Datenbank-Spektrum, 2002.
12. G. Hetzel, B. Leibe, P. Levi, and B. Schiele. 3D object recognition from range images using local feature histograms. In CVPR, volume 2, pages 394-399. IEEE, 2001.
13. D. Huber, A. Kapuria, R. Donamukkala, and M. Hebert. Parts-based 3d object classification. In CVPR, volume 2. IEEE, 2004.
14. A. E. Johnson and M. Hebert. Using spin images for efficient object recognition in cluttered 3D scenes. PAMI, 21(5):433, 1999.
15. J. Koenderink and A. van Doorn. Surface shape and curvature scales. Image and vision computing, 10(8):557-564, 1992.
16. M. K̈ortgen, G. Park, M. Novotni, and R. Klein. 3D shape matching with 3D shape contexts. In CESCG, volume 3. Citeseer, 2003.
17. K. Lai, L. Bo, X. Ren, and D. Fox. A Large-Scale Hierarchical Multi-View RGB-D Object Dataset. In ICRA, 2011.
18. A. Opelt and M. Fussenegger. Weak hypotheses and boosting for generic object detection and recognition. ECCV, 2004.
19. R. Osada, T. Funkhouser, B. Chazelle, and D. Dobkin. Shape distributions. ACM Transactions on Graphics, 21(4):807-832, Oct. 2002.
20. U. Reiser, C. Connette, J. Fischer, J. Kubacki, A. Bubeck, F. Weisshardt, T. Jacobs, C. Parlitz, M. Ḧagele, and A. Verl. Care-O-bot 3: creating a product vision for service robot applications by integrating design and technology. In IROS, pages 1992-1998. IEEE Press, 2009.
21. S. Ruiz-correa, L. G. Shapiro, and M. Meil. A new paradigm for recognizing 3-D objects from range data. ICCV, pages 1126-1133 vol. 2, 2003.
22. E. Shechtman and M. Irani. Matching local self-similarities across images and videos. In CVPR, pages 1-8, 2007.
23. M. Sun, G. Bradski, B.-X. Xu, and S. Savarese. Depthencoded hough voting for coherent object detection, pose estimation, and shape recovery. In ECCV, 2010.