Local Discriminant Wavelet Packet Coordinates for Face Recognition
The Journal of Machine Learning Research
Intra-dimensional feature diagnosticity in the Fuzzy Feature Contrast Model
Image and Vision Computing
Smart image search by boosted shape features
ICAI'06 Proceedings of the 7th WSEAS International Conference on Automation & Information
Relevance aggregation projections for image retrieval
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Feature selection based-on genetic algorithm for image annotation
Knowledge-Based Systems
Online Feature Selection Algorithm with Bayesian l 1 Regularization
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Efficient entropy-based features selection for image retrieval
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Online learning of relevance feedback from expert readers for mammogram retrieval
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Medical image retrieval, indexing and enhancement techniques: a survey
Proceedings of the 2011 International Conference on Communication, Computing & Security
Feature subspace selection for efficient video retrieval
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Online modeling of proactive moderation system for auction fraud detection
Proceedings of the 21st international conference on World Wide Web
Visual query processing for efficient image retrieval using a SOM-based filter-refinement scheme
Information Sciences: an International Journal
A new matching strategy for content based image retrieval system
Applied Soft Computing
A novel framework for concept detection on large scale video database and feature pool
Artificial Intelligence Review
Feature subset selection using improved binary gravitational search algorithm
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Content-based image retrieval (CBIR) has been more and more important in the last decade, and the gap between high-level semantic concepts and low-level visual features hinders further performance improvement. The problem of online feature selection is critical to really bridge this gap. In this paper, we investigate online feature selection in the relevance feedback learning process to improve the retrieval performance of the region-based image retrieval system. Our contributions are mainly in three areas. 1) A novel feature selection criterion is proposed, which is based on the psychological similarity between the positive and negative training sets. 2) An effective online feature selection algorithm is implemented in a boosting manner to select the most representative features for the current query concept and combine classifiers constructed over the selected features to retrieve images. 3) To apply the proposed feature selection method in region-based image retrieval systems, we propose a novel region-based representation to describe images in a uniform feature space with real-valued fuzzy features. Our system is suitable for online relevance feedback learning in CBIR by meeting the three requirements: learning with small size training set, the intrinsic asymmetry property of training samples, and the fast response requirement. Extensive experiments, including comparisons with many state-of-the-arts, show the effectiveness of our algorithm in improving the retrieval performance and saving the processing time.