International Journal of Computer Vision
Representation and recognition in vision
Representation and recognition in vision
Visual Recognition and Categorization on the Basis of Similarities to Multiple Class Prototypes
International Journal of Computer Vision
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Databases: Search and Retrieval of Digital Imagery
Image Databases: Search and Retrieval of Digital Imagery
International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Feature Discovery in Non-Metric Pairwise Data
The Journal of Machine Learning Research
A Generic Scheme for Color Image Retrieval Based on the Multivariate Wald-Wolfowitz Test
IEEE Transactions on Knowledge and Data Engineering
Semiology of graphics
Computer Vision and Image Understanding
On the information and representation of non-Euclidean pairwise data
Pattern Recognition
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Perceptually near pawlak partitions
Transactions on rough sets XII
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A human-centered approach to image database organization is presented in this study. The management of a generic image database is pursued using a standard psychophysical experimental procedure followed by a well-suited data analysis methodology that is based on simple geometrical concepts. The end result is a cognitive discriminative biplot, which is a visualization of the intrinsic organization of the image database best reflecting the user's perception. The discriminating power of the introduced cognitive biplot constitutes an appealing tool for image retrieval and a flexible interface for visual data mining tasks. These ideas were evaluated in two ways. First, the separability of semantically distinct image classes was measured according to their reduced representations on the biplot. Then, a nearest-neighbor retrieval scheme was run on the emerged low-dimensional terrain to measure the suitability of the biplot for performing content-based image retrieval (CBIR). The achieved organization performance when compared with the performance of a contemporary system was found superior. This promoted the further discussion of packing these ideas into a realizable algorithmic procedure for an efficient and effective personalized CBIR system.