Using stereo for object recognition

Proceedings - IEEE International Conference on Robotics and Automation

Volumn , Issue , 2010, Pages 3121-3127

  Helmer, Scott ^a   Lowe, David ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

APPEARANCE-BASED RECOGNITION; DATA SETS; DEPTH INFORMATION; DISTINCTIVE FEATURES; FALSE POSITIVE; MOBILE ROBOTIC; OBJECT CLASS; ROBUST RECOGNITION; VISUAL SEARCH;

OBJECT RECOGNITION; ROBOTS; STEREO VISION;

ROBOTICS;

EID: 77955834995     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROBOT.2010.5509826     Document Type: Conference Paper

References (24)

1. P. F. Felzenszwalb and D. A. M. and Deva Ramanan, "A discriminatively trained, multiscale, deformable part model," in CVPR, 2008.
2. M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman, "The PASCAL Visual Object Classes Challenge 2008 (VOC2008) Results," http://www.pascal-network.org/challenges/VOC/voc2008/workshop/index.html.
3. A. Torralba, "Contextual priming for object detection," IJCV, vol. 53(2), pp. 169-191, 2003.
4. J. Shotton, J. Winn, C. Rother, and A. Criminisi, "Textonboost: Joint appearance, shape and context modeling for multi-class object recognition," in ECCV, 2006.
5. A. Torralba, K. Murphy, and W. Freeman., "Contextual models for object detection using boosted random fields," in NIPS, 2005.
6. D. Parikh, L. Zitnick, and T. Chen., "From appearance to context-based recognition: Dense labeling in small images," in CVPR, 2008.
7. S. Kumar and M. Hebert, "A hierarchical field framework for unified context-based classification," in ICCV, 2005.
8. D. Hoiem, A. Efros, and M. Heber, "Putting objects in perspective," in CVPR, 2006.
9. B. Leibe, N. Cornelis, K. Cornelis, and L. Gool, "Dynamic 3d scene analysis from a moving vehicle," in CVPR, 2007.
10. S. Gould, P. Baumstarck, M. Quigley, , A. Y. Ng, and D. Koller, "Integrating visual and range data for robotic object detection," in ECCV Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2), 2008.
11. G. J. Brostow, J. Shotton, J. Fauqueur, , and R. Cipolla, "Segmentation and recognition using structure from motion cues," in ECCV, 2008.
12. E. B. Sudderth, A. Torralba, W. T. Freeman, and A. S. Willsky, "Depth from familiar objects: A hierarchical model for 3d scenes," in CVPR, 2006.
13. M. Quigley, S. Batra, S. Gould, E. Klingbeil, Q. Le, A. Wellman, and A. Y. Ng, "High-accuracy 3d sensing for mobile manipulation: Improving object detection and door opening," in International Conference on Robotics and Automation, 2009.
14. D. Meger, P.-E. Forssén, K. Lai, S. Helmer, S. McCann, T. Southey, M. A. Baumann, J. J. Little, and D. G. Lowe, "Curious george: An attentive semantic robot," Robotics and Autonomous Systems, vol. 56, no. 6, pp. 503-511, 2008.
15. S. M. Dariu M. Gavrila, "Multi-cue pedestrian detection and tracking from a moving vehicle," IJCV, vol. 73 (1), pp. 41-59, 2007.
16. J. Shotton and R. Blake, A.and Cipolla, "Multi-scale categorical object recognition using contour fragments," PAMI, 2007.
17. A. Opelt, A. Pinz, and A. Zisserman, "A boundary fragment model for object detection," in ECCV, 2006.
18. D. M. Gavrila, "A bayesian, exemplar-based approach to hierarchical shape matching," PAMI, vol. 29 (8), pp. 1408-1421, 2007.
19. M. P. Kumar, P. Torr, and A. Zisserman, "Extending pictorial structures for object recognition," in BMVC, 2004.
20. B. Leibe, E. Seeman, and B. Schiele, "Pedestrian detection in crowded scenes," in CVPR, 2005.
21. H. Barrow, J. Tenenbaum, R. Bolles, and H. Wolf., "Parametric correspondence and chamfer matching: Two new techniques for image matching," in IJCAI, 1977.
22. A. Opelt, A. Pinz, and A. Zisserman, "Incremental learning of object detectors using a visual shape alphabet," in CVPR, 2006.
23. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," IJCV, vol. 60(2), pp. 91-110, 2004.
24. R. I. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd ed. Cambridge University Press, ISBN: 0521540518, 2004.