Learning structured appearance models from captioned images of cluttered scenes

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2007, Pages

  Jamieson, Michael ^a   Fazly, Afsaneh ^a   Dickinson, Sven ^a   Stevenson, Suzanne ^a   Wachsmuth, Sven ^b  

^a UNIVERSITY OF TORONTO   (Canada)

^b BIELEFELD UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

APPEARANCE MODELING; CLUTTERED SCENES; INTERNATIONAL CONFERENCES;

COMPUTER NETWORKS; COMPUTER VISION;

IMAGE ENHANCEMENT;

EID: 50649100341     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2007.4408877     Document Type: Conference Paper

References (14)

1. K. Barnard and D. Forsyth. Learning the semantics of words and pictures. In ICCV-01. 1
2. T. L. Berg, A. C. Berg, J. Edwards, M. Maire, R. White, Y.-W. Teh, E. Learned-Miller, and D. Forsyth. Names and faces in the news. In CVPR-04. 2
3. G. Carniero and A. Jepson. Flexible spatial models for grouping local image features. In CVPR-04. 3
4. G. Carniero and N. Vasconcelos. Formulating semantic image annotation as a supervised learning problem. In CVPR-05. 1
5. M. L. Cascia, S. Sethi, and S. Sclaroff. Combining textual and visual cues for content-based image retrieval on the World Wide Web. In Proc. of IEEE Workshop on Content-based Access of Image and Video Libraries, 1998.
6. D. J. Crandall and D. P. Huttenlocher. Weakly supervised learning of part-based spatial models for visual object recognition. In ECCV-06. 2
7. P. Duygulu, K. Barnard, J. F. G. de Freitas, and D. Forsyth. Object recognition as machine translation: Learning a lexicon for a fixed image vocabulary. In ECCV-02. 1, 2
8. S. L. Feng, R. Manmatha, and V. Lavrenko. Multiple Bernoulli relevance models for image and video annotation. In CVPR-04. 1
9. R. Fergus, L. Fei-Fei, P. Perona, and A. Zisserman. Learning object categories from Google's image search. In CVPR-05. 2
10. M. Jamieson, S. Dickinson, S. Stevenson, and S. Wachsmuth. Using language to drive the perceptual grouping of local image features. In CVPR-06. 1, 2, 3, 5, 6
11. Y. Ke and R. Sukthankar. PCA-SIFT: A more distinctive representation for local image descriptors. In CVPR-04. 3
12. D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2):91-110, 2004.
13. J. Sivic and A. Zisserman. Video data mining using configurations of viewpoint invariant regions. In CVPR-04. 3, 5
14. S. Wachsmuth, S. Stevenson, and S. Dickinson. Towards a framework for learning structured shape models from text-annotated images. In HLT-NAACL03 Workshop on Learning Word Meaning from Non-Linguistic Data, 2003.