Does relevance feedback improve document retrieval performance?
SIGIR '78 Proceedings of the 1st annual international ACM SIGIR conference on Information storage and retrieval
Integrating Unlabeled Images for Image Retrieval Based on Relevance Feedback
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Content-based sub-image retrieval using relevance feedback
Proceedings of the 2nd ACM international workshop on Multimedia databases
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human-centered multimedia: representations and challenges
Proceedings of the 1st ACM international workshop on Human-centered multimedia
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Performance evaluation of relevance feedback methods
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Pedestrian Detection via Classification on Riemannian Manifolds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Query Point Movement Techniques for Large CBIR Systems
IEEE Transactions on Knowledge and Data Engineering
Graph-based transductive learning for robust visual tracking
Pattern Recognition
Mean shift feature space warping for relevance feedback
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Surfing on artistic documents with visually assisted tagging
Proceedings of the international conference on Multimedia
Automatic segmentation of digitalized historical manuscripts
Multimedia Tools and Applications
Toward consistent evaluation of relevance feedback approaches in multimedia retrieval
AMR'05 Proceedings of the Third international conference on Adaptive Multimedia Retrieval: user, context, and feedback
Interactive Search by Direct Manipulation of Dissimilarity Space
IEEE Transactions on Multimedia
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This paper provides an analysis on relevance feedback techniques in a multimedia system designed for the interactive exploration and annotation of artistic collections, in particular illuminated manuscripts. The relevance feedback is presented not only as a very effective technique to improve the performance of the system, but also as a clever way to increase the user experience, mixing the interactive surfing through the artistic content with the possibility to gather valuable information from the user, and consequently improving his retrieval satisfaction. We compare a modification of the Mean-Shift Feature Space Warping algorithm, as representative of the standard RF procedures, and a learning-based technique based on transduction, considered in order to overcome some limitation of the previous technique. Experiments are reported regarding the adopted visual features based on covariance matrices.