Free-shape subwindow search for object localization

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

Volumn , Issue , 2010, Pages 1086-1093

  Zhang, Zhiqi ^a   Cao, Yu ^a   Salvi, Dhaval ^a   Oliver, Kenton ^a   Waggoner, Jarrell ^a   Wang, Song ^a  

^a University of South Carolina   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAG-OF-VISUAL WORDS; CONTOUR GRAPH; EDGE PIXELS; GRAPH THEORETIC APPROACH; OBJECT LOCALIZATION; OBJECT OF INTERESTS; OBJECTIVE FUNCTIONS; SEARCH ALGORITHMS; WELL-ALIGNED;

ANIMALS; COMPUTER VISION; GRAPH THEORY; LEARNING ALGORITHMS; OBJECT RECOGNITION;

OPTIMIZATION;

EID: 77956004769     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2010.5540095     Document Type: Conference Paper

References (27)

1. S. An, P. Peursum, W. Liu, and S. Venkatesh. Efficient algorithms for subwindow search in object detection and localization. In CVPR, 2009.
2. A. Bosch, A. Zisserman, and X. Munoz. Representing shape with a spatial pyramid kernel. In ACM Intl. Conf. on Image & Video Retrieval, pages 401-408, 2007.
3. J. Canny. A computational approach to edge detection. IEEE-TPAMI, 8(6):679-698, 1986.
4. O. Chum and A. Zisserman. An exemplar model for learning object class. In CVPR, 2007.
5. M. Dundar and J. Bi. Joint optimization of cascaded classifiers for computer aided detection. In CVPR, 2007.
6. P. F. Felzenszwalb, R. B. Girshick, D. Mcallester, and D. Ramanman. Object detection with discriminatively trained part based model. IEEE-TPAMI, 2009.
7. V. Ferrari, L. Fevrier, F. Jurie, and C. Schmid. Groups of adjacent contour segments for object detection. IEEE-TPAMI, 30(1):36-51, 2008.
8. M. Fritz and B. Schiele. Decomposition, discovery and detection of visual categories using topic models. In CVPR, 2008.
9. J. C. V. Gemert, J. M. Geusebroek, C. J. Veenman, and A. W. M. Smeulders. Kernel codebooks for scene categorization. In ECCV, 2008.
10. H. Harazllah, F. Jurie, and C. Schmid. Combining efficient object localization and image classification. In ICCV, 2009.
11. G. Heitz and D. Koller. Learning spatial context: using stuff to find things. In ECCV, 2008.
12. P. D. Kovesi. MATLAB and Octave functions for computer vision and image processing. Available from: 〈http://www.csse.uwa.edu.au/~pk/research/ matlabfns/〉.
13. C. H. Lampert, M. B. Blaschko, and T. Hofmann. Beyond sliding windows: Object localization by efficient subwindow search. In CVPR, 2008.
14. S. Lazebnik, C. Schmid, and J. Ponce. Beyong bags of feature: Spatial pyramid matching for recognizing. In CVPR, 2006.
15. B. Leibe, A. Leonardis, and B. Schiele. Robust object detection with interleaved categorization and segmentation. IJCV, 77(1):259-289, 2008.
16. D. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2):91-110, 2004.
17. M. Maire, P. Arbelaez, C. Fowlkes, and J. Malik. Using contours to detect and localize junctions in natural images. In CVPR, 2008.
18. C. Pantofaru, C. Schmid, and M. Herbert. Object recognition by integrating multiple image segmentations. In ECCV, 2008.
19. F. Perronnin. Universal and adapted vocabularies for generic visual categorization. IEEE-TPAMI, 30(7):1243-1256, 2008.
20. B. Scholkopf and A. Smola. Learning with kernel. MIT Press, 2002.
21. J. S. Stahl, K. Oliver, and S. Wang. Open boundary capable edge grouping with feature maps. In POCV, 2008.
22. J. S. Stahl and S.Wang. Edge grouping combining boundary and region information. IEEE-TPAMI, 16(10):2590-2606, 2007.
23. J. Verbeek and B. Triggs. Region classification with markov field aspect models. In CVPR, 2007.
24. P. Viola and M. J. Jones. Robust real-time face detection. IJCV, 57(2):137-154, 2004.
25. S. Wang, T. Kubota, J. Siskind, and J. Wang. Salient closed boundary extraction with ratio contour. IEEE-TPAMI, 27(4):546-561, 2005.
26. T. Yeh, J. Lee, and T. Darrell. Fast concurrent object localization and recognition. In CVPR, 2009.
27. J. Zhang, M. Marszalek, S. Lazebnik, and C. Schmid. Local features and kernels for classification of texture and object categories: a comprehensive study. IJCV, 73(2):213-238, 2007.