Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
IEEE Transactions on Pattern Analysis and Machine Intelligence
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Support vector machine active learning for image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
A Min-max Cut Algorithm for Graph Partitioning and Data Clustering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Content-Based Image Retrieval Using Self-Organizing Maps
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
Bayesian Relevance Feedback for Content-Based Image Retrieval
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
An Optimized Interaction Strategy for Bayesian Relevance Feedback
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Multiclass Spectral Clustering
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Learning from User Behavior in Image Retrieval: Application of Market Basket Analysis
International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Manifold-ranking based image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
Learning an image manifold for retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
A novel log-based relevance feedback technique in content-based image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
A discriminative learning framework with pairwise constraints for video object classification
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
CLUE: cluster-based retrieval of images by unsupervised learning
IEEE Transactions on Image Processing
Learning a semantic space from user's relevance feedback for image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
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One of the keys issues to content-based image retrieval is the similarity measurement of images. Images are represented as points in the space of low-level visual features and most similarity measures are based on certain distance measurement between these features. Given a distance metric, two images with shorter distance are deemed to more similar than images that are far away. The well-known problem with these similarity measures is the semantic gap, namely two images separated by large distance could share the same semantic content. In this paper, we propose a novel similarity measure of images that goes beyond the distance measurement. The key idea is to exploit the clustering structure of images when a large number of images are present. The similarity of two images is determined not only by their Euclidean distance in the space of visual features but also by the likelihood for them to be clustered together, which is further estimated using a marginalized kernel. Our empirical studies with COREL datasets have shown that the proposed similarity measure is effective for traditional content-based image retrieval as well as user relevance feedback.