Annotating photo collections by label propagation according to multiple similarity cues

MM'08 - Proceedings of the 2008 ACM International Conference on Multimedia, with co-located Symposium and Workshops

Volumn , Issue , 2008, Pages 121-129

  Cao, Liangliang ^a   Luo, Jiebo ^b   Huang, Thomas S ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b EASTMAN KODAK COMPANY   (United States)

Author keywords

Color histogram; GPS; Label propagation; Photo collection; Photo similarities; SIFT; Timestamp

Indexed keywords

COLOR HISTOGRAM; GPS; LABEL PROPAGATION; PHOTO COLLECTION; PHOTO SIMILARITIES; SIFT; TIMESTAMP;

CAMERAS; GLOBAL POSITIONING SYSTEM; IMAGE RETRIEVAL; LABELS; METHOD OF MOMENTS; MULTIMEDIA SYSTEMS;

COMPUTER GRAPHICS;

EID: 70350662970     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1459359.1459376     Document Type: Conference Paper

References (29)

1. Flickr, http://www.flickr.com
2. Picasa Web Album, http://picasaweb.google.com
3. Corel stock photo database, http://www.corel.com
4. L. Fei-Fei and P. Perona. A Bayesian hierarchical model for learning natural scene categories, IEEE Proc. Computer Vision and Pattern Recognition, 2005.
5. A. K. Jain and A. Vailaya, Image retrieval using color and shape, Pattern Recognition, 29 (8), 1233-1244, 1996.
6. Y. Rui, T.S. Huang, S Mehrotra, Content-based image retrieval with relevance feedback in MARS, IEEE Proc. Image Processing, 1997.
7. A. Blum, T. Mitchell, Combining labeled and unlabeled data with co-training, Annual Conference on Learning Theory, 1998.
8. S. Tong, E. Chang, Support vector machine active learning for image retrieval, ACM Conf. Multimedia, 2001.
9. S. Hoi, M.R. Lyu, A semi-supervised active learning framework for image retrieval, IEEE Proc. Computer Vision and Pattern Recognition, 2005.
10. G. Carneiro, A. B. Chan, P. J. Moreno, N. Vasconcelos, Supervised Learning of Semantic Classes for Image Annotation and Retrieval, IEEE Trans. Pattern Analysis and Machine Intelligence, 2007.
11. X. Zhu, Z. Ghahramani, and J. Lafferty, Semi-supervised learning using Gaussian fields and harmonic functions, International Conference on Machine Learning, 2003.
12. F. Wang, C. Zhang, H.C. Shen, and J. Wang, Semi-Supervised Classification Using Linear Neighborhood Propagation, IEEE Proc. Computer Vision and Pattern Recognition, 2006.
13. D. Zhou , O. Bousquet, T.N. Lal, J. Weston and B. Scholkopf, Learning with Local and Global Consistency. Neural Information Processing Systems, 2004.
14. J. He, M. Li, H.-J. Zhang, H. Tong, C. Zhang , Manifold-ranking based image retrieval, ACM Conf. Multimedia, 2004.
15. J. Liu, M Li, W.Y. Ma, Q. Liu, H. Lu, An adaptive graph model for automatic image annotation, ACM workshop on Multimedia Information Retrieval, 2006.
16. H. Tong, J. He, M. Li, C Zhang, W-Y. Ma, Graph based multi-modality learning, ACM Conf. Multimedia, 2005.
17. J. Liu, W. Lai, X-S Hua, Y Huang, and S. Li. Video Search Re-Ranking via Multi-Graph Propagation. ACM Conf. Multimedia, 2007.
18. D. Zhou and C. Burges, Spectral Clustering and Transductive Learning with Multiple Views. International Conference on Machine Learning, 2007.
19. D. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, 60(2): 91-110, International Journal of Computer Vision, 2004.
20. Matthew Brown and David G. Lowe, Automatic panoramic image stitching using invariant features, International Journal of Computer Vision, 74(1): 59-73, 2007.
21. M. Boutell, and J. Luo. Beyond pixels: Exploiting camera metadata for photo classification. Pattern Recognition 38(6): 935-946, 2005.
22. Y. Aytar, O.B. Orhan, and M. Shah. Improving Semantic Concept Detection and Retrieval Using Contextual Estimates, IEEE International Conference on Multimedia & Expo, 2007.
23. T. Joachims. Making large scale SVM learning practical, Advances in Kernel Methods - Support Vector Learning, MIT-Press, 1999.
24. Y. Wang, H. Zhang. Detecting image orientation based on low-level visual content. Computer Vision and Image Understanding 93(3): 328-346, 2004.
25. D. Tao, X. Tang, X. Li, and X. Wu. Asymmetric Bagging and Random Subspace for Support Vector Machines-based Relevance Feedback in Image Retrieval, IEEE Trans. Pattern Analysis and Machine Intelligence, 28(7): 1088-1099, 2006.
26. P. Quelhas, et. al., Modeling Scenes with Local Descriptors and Latent Aspects, IEEE Proc. International Conference on Computer Vision, 2005.
27. S.F. Chang, et. al., Columbia Univ. TRECVID-2005 Video Search and High-Level Feature Extraction, Proc. TREC Video Retrieval Evaluation, 2005.
28. M. Campbell, et. al., IBM Research TRECVID-2006 Video Retrieval System, Proc. TREC Video Retrieval Evaluation, 2006.
29. M. Boutell and J. Luo, Beyond Pixels: Exploiting camera metadata for photo classification, Pattern Recognition 38(6): 935-946, 2005.