Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Iterative refinement by relevance feedback in content-based digital image retrieval
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
WALRUS: a similarity retrieval algorithm for image databases
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Visual information retrieval
A relevance feedback mechanism for content-based image retrieval
Information Processing and Management: an International Journal
Algorithms for Defining Visual Regions-of-Interest: Comparison with Eye Fixations
IEEE Transactions on Pattern Analysis and Machine Intelligence
How to solve it: modern heuristics
How to solve it: modern heuristics
IRM: integrated region matching for image retrieval
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principles of visual information retrieval
Principles of visual information retrieval
Relevance feedback techniques in image retrieval
Principles of visual information retrieval
Information Theoretic Measure for Visual Target Distinctness
IEEE Transactions on Pattern Analysis and Machine Intelligence
FIRM: fuzzily integrated region matching for content-based image retrieval
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Multimedia Tools and Applications
Emergent Semantics through Interaction in Image Databases
IEEE Transactions on Knowledge and Data Engineering
A Region-Based Fuzzy Feature Matching Approach to Content-Based Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
MindReader: Querying Databases Through Multiple Examples
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
FALCON: Feedback Adaptive Loop for Content-Based Retrieval
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Genetic algorithm-based relevance feedback for image retrieval using local similarity patterns
Information Processing and Management: an International Journal
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)
Exploring the Nature and Variants of Relevance Feedback
CBAIVL '01 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'01)
NeTra: a toolbox for navigating large image databases
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Modified hierarchical genetic algorithm for relevance feedback in image retrieval
Intelligent Data Analysis
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Weighted Local Similarity Pattern (WLSP)} is proposed as a new image similarity model, which considers two fundamental properties of the human visual system: (1) saliency of regions within an image, and (2) saliency of features within each region. Furthermore, since both region and feature saliencies are context dependent, genetic algorithm (GA)-based relevance feedback mechanism is proposed to automatically infer the (sub-)optimal assignment of the two saliencies, based on the query image and the set of relevant images, provided by the user. None of the existing image similarity models considers both region and feature saliencies in a context-dependent sense, allowing their automatic inference. In addition, this paper is the first to explicitly discuss the implications of the region and feature saliency properties to the design of an image similarity model, in the framework of image retrieval. The proposed method - including the WLSP image similarity model and the GA-based relevance feedback mechanism - is evaluated on five test databases, with around 2,500 images, covering 62 semantic categories. Compared with eleven of the representative image similarity models, including three based on relevance feedback, the proposed model brings in average between 6% and 30% increase in the retrieval precision. Results suggest that considering region and feature saliencies in a context-dependent sense enables the image similarity model to more accurately capture the human similarity perception.