Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
A signal-to-noise approach to score normalization
Proceedings of the 18th ACM conference on Information and knowledge management
Content based radiology image retrieval using a fuzzy rule based scalable composite descriptor
Multimedia Tools and Applications
Image retrieval based on similarity score fusion from feature similarity ranking lists
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Dynamic two-stage image retrieval from large multimodal databases
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Fusion vs. two-stage for multimodal retrieval
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Dynamic two-stage image retrieval from large multimedia databases
Information Processing and Management: an International Journal
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Compact composite descriptors (CCDs) are global image features, capturing more than one types of information at the same time in a very compact representation. Their quality has so far been evaluated in retrieval from several homogeneous databases containing images of only the type that each CCD is intended for, and has been found better than other descriptors in the literature such as the MPEG-7 descriptors. In this study, we consider heterogeneous databases and investigate query-time fusion techniques for CCDs. The results show that fusion is beneficial, even with simple score normalization and combination methods due to the compatibility of the score distributions produced by the CCDs considered.