Image categorization using directed graphs

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6313 LNCS, Issue PART 3, 2010, Pages 762-775

  Wang, Hua ^a   Huang, Heng ^a   Ding, Chris ^a  

^a University of Texas at Arlington   (United States)

Author keywords

Co linkage similarity; Directed graph learning; Image annotation; Multi label classification; Object Recognition

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER VISION; GRAPHIC METHODS; IMAGE ANALYSIS; IMAGE ANNOTATION; IMAGING SYSTEMS; OBJECT RECOGNITION; SUPERVISED LEARNING;

EDGE WEIGHTS; EMPIRICAL STUDIES; GRAPH-CONSTRUCTION METHOD; IMAGE CATEGORIZATION; MULTI LABEL CLASSIFICATION; SEMI-SUPERVISED CLASSIFICATION METHOD; STRUCTURAL INFORMATION; UNDIRECTED GRAPH;

DIRECTED GRAPHS;

EID: 78149341724     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15558-1_55     Document Type: Conference Paper

References (21)

1. Agarwal, S., Roth, D.: Learning a sparse representation for object detection. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2353, pp. 113-127. Springer, Heidelberg (2002)
2. Belkin, M., Niyogi, P.: Laplacian eigenmaps for dimensionality reduction and data representation. Neural computation 15(6), 1373-1396 (2003) (Pubitemid 37049796)
3. Cheng, H., Liu, Z., Yang, J.: Sparsity Induced Similarity Measure for Label Propagation. In: IEEE ICCV (2009)
4. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE CVPR (2005)
5. Ding, C., He, X., Husbands, P., Zha, H., Simon, H.: PageRank, HITS and a unified framework for link analysis. In: ACM SIGIR (2002)
6. Ding, C., Simon, H., Jin, R., Li, T.: A learning framework using Green's function and kernel regularization with application to recommender system. In: ACM SIGKDD (2007)
7. Ding, C., Zha, H., He, X., Husbands, P., Simon, H.: Link analysis: hubs and authorities on the World Wide Web. SIAM Review (2004)
8. Elhamifar, E., Vidal, R.: Sparse subspace clustering. In: IEEE CVPR (2009)
9. Hull, J.: A database for handwritten text recognition research. IEEE TPAMI 16(5), 550-554 (1994)
10. Kleinberg, J.: Authoritative sources in a hyperlinked environment. Journal of the ACM 46(5), 604-632 (1999)
11. Leibe, B., Schiele, B.: Analyzing appearance and contour based methods for object categorization. In: IEEE CVPR (2003)
12. Lewis, D., Yang, Y., Rose, T., Li, F.: Rcv1: A new benchmark collection for text categorization research. Journal of Machine Learning Research 5, 361-397 (2004)
13. Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: Bringing order to the web. Stanford Digital Library Technologies Project (1998)
14. Rao, R., Olshausen, B., Lewicki, M.: Probabilistic models of the brain: Perception and neural function (2002)
15. Wang, F., Zhang, C.: Label propagation through linear neighborhoods. In: ICML (2006)
16. Wang, H., Huang, H., Ding, C.: Image Annotation Using Multi-label Correlated Greens Function. In: IEEE ICCV (2009)
17. Wright, J., Yang, A., Ganesh, A., Sastry, S., Ma, Y.: Robust face recognition via sparse representation. IEEE TPAMI, 210-227 (2009)
18. Yan, S., Wang, H.: Semi-supervised learning by sparse representation. In: SDM (2009)
19. Yang, W., Zhang, S., Liang, W.: A Graph Based Subspace Semi-supervised Learning Framework for Dimensionality Reduction. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part II. LNCS, vol. 5303, pp. 664-677. Springer, Heidelberg (2008)
20. Zhou, D., Bousquet, O., Lal, T., Weston, J., Schölkopf, B.: Learning with local and global consistency. In: NIPS (2004)
21. Zhu, X., Ghahramani, Z., Lafferty, J.: Semi-supervised learning using Gaussian fields and harmonic functions. In: ICML (2003)