Unsupervised learning by probabilistic latent semantic analysis
Machine Learning
Extrapolation methods for accelerating PageRank computations
WWW '03 Proceedings of the 12th international conference on World Wide Web
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
GCap: Graph-based Automatic Image Captioning
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 9 - Volume 09
Updating Markov Chains with an Eye on Google's PageRank
SIAM Journal on Matrix Analysis and Applications
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Imagerank: spectral techniques for structural analysis of image database
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Video search reranking through random walk over document-level context graph
Proceedings of the 15th international conference on Multimedia
Generating diverse and representative image search results for landmarks
Proceedings of the 17th international conference on World Wide Web
A Discriminative Kernel-Based Approach to Rank Images from Text Queries
IEEE Transactions on Pattern Analysis and Machine Intelligence
VisualRank: Applying PageRank to Large-Scale Image Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning tag relevance by neighbor voting for social image retrieval
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Proceedings of the 18th international conference on World wide web
Proceedings of the 18th international conference on World wide web
Multilayer pLSA for multimodal image retrieval
Proceedings of the ACM International Conference on Image and Video Retrieval
Multimodal pLSA on visual features and tags
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
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Searching for relevant images given a query term is an important task in nowadays large-scale community databases. The image ranking approach presented in this work represents an image collection as a graph that is built using a multimodal similarity measure based on visual features and user tags. We perform a random walk on this graph to find the most common images. Further we discuss several scalability issues of the proposed approach and show how in this framework queries can be answered fast. Experimental results validate the effectiveness of the presented algorithm.