Content-based image retrieval: approaches and trends of the new age
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
A survey of content-based image retrieval with high-level semantics
Pattern Recognition
Retrieval of images of man-made structures based on projective invariance
Pattern Recognition
Content-based object organization for efficient image retrieval in image databases
Decision Support Systems
Adaptive salient block-based image retrieval in multi-feature space
Image Communication
Learning user intention in relevance feedback using optimization
Proceedings of the international workshop on Workshop on multimedia information retrieval
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Mining user hidden semantics from image content for image retrieval
Journal of Visual Communication and Image Representation
Relevance feedback for category search in music retrieval based on semantic concept learning
Multimedia Tools and Applications
A Hybrid Region Weighting Approach for Relevance Feedback in Region-Based Image Search on the Web
SOFSEM '07 Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science
A new relevance feedback technique for iconic image retrieval based on spatial relationships
Journal of Systems and Software
Interactive objects retrieval with efficient boosting
MM '09 Proceedings of the 17th ACM international conference on Multimedia
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
Region-based image retrieval system with heuristic pre-clustering relevance feedback
Expert Systems with Applications: An International Journal
Semantic image retrieval using region-based relevance feedback
AMR'06 Proceedings of the 4th international conference on Adaptive multimedia retrieval: user, context, and feedback
Relevance feedback using adaptive clustering for region based image similarity retrieval
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Modeling user feedback using a hierarchical graphical model for interactive image retrieval
PCM'07 Proceedings of the multimedia 8th Pacific Rim conference on Advances in multimedia information processing
A relevance feedback method based on genetic programming for classification of remote sensing images
Information Sciences: an International Journal
Sparse based image classification with different keypoints descriptors
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
An academic information retrieval system based on multiagent framework
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
Heuristic pre-clustering relevance feedback in region-based image retrieval
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Using relevance feedback to bridge the semantic gap
AMR'05 Proceedings of the Third international conference on Adaptive Multimedia Retrieval: user, context, and feedback
k-Partite graph reinforcement and its application in multimedia information retrieval
Information Sciences: an International Journal
Multimedia Tools and Applications
Multifeature analysis and semantic context learning for image classification
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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Relevance feedback and region-based representations are two effective ways to improve the accuracy of content-based image retrieval systems. Although these two techniques have been successfully investigated and developed in the last few years, little attention has been paid to combining them together. We argue that integrating these two approaches and allowing them to benefit from each other will yield better performance than using either of them alone. To do that, on the one hand, two relevance feedback algorithms are proposed based on region representations. One is inspired from the query point movement method. By assembling all of the segmented regions of positive examples together and reweighting the regions to emphasize the latest ones, a pseudo image is formed as the new query. An incremental clustering technique is also considered to improve the retrieval efficiency. The other is the introduction of existing support vector machine-based algorithms. A new kernel is proposed so as to enable the algorithms to be applicable to region-based representations. On the other hand, a rational region weighting scheme based on users' feedback information is proposed. The region weights that somewhat coincide with human perception not only can be used in a query session, but can also be memorized and accumulated for future queries. Experimental results on a database of 10 000 general-purpose images demonstrate the effectiveness of the proposed framework.