Asymmetric Learning and Dissimilarity Spaces for Content-Based Retrieval
نویسندگان
چکیده
This paper presents novel dissimilarity space specially designed for interactive multimedia retrieval. By providing queries made of positive and negative examples, the goal consists in learning the positive class distribution. This classification problem is known to be asymmetric, i.e. the negative class does not cluster in the original feature spaces. We introduce here the idea of Query-based Dissimilarity Space (QDS) which enables to cope with the asymmetrical setup by converting it in a more classical 2-class problem. The proposed approach is evaluated on both artificial data and real image database, and compared with stateof-the-art algorithms.
منابع مشابه
Further results on dissimilarity spaces for hyperspectral images RF-CBIR
Content-Based Image Retrieval (CBIR) systems are powerful search tools in image databases that have been little applied to hyperspectral images. Relevance Feedback (RF) is an iterative process that uses machine learning techniques and user’s feedback to improve the CBIR systems performance. We pursued to expand previous research in hyperspectral CBIR systems built on dissimilarity functions def...
متن کاملComparing Dissimilarity Measures for Content-Based Image Retrieval
Dissimilarity measurement plays a crucial role in contentbased image retrieval, where data objects and queries are represented as vectors in high-dimensional content feature spaces. Given the large number of dissimilarity measures that exist in many fields, a crucial research question arises: Is there a dependency, if yes, what is the dependency, of a dissimilarity measure’s retrieval performan...
متن کاملThe Open University ’ s repository of research publications and other research outputs Dissimilarity measures for content - based image retrieval
Dissimilarity measurement plays a crucial role in contentbased image retrieval. In this paper, 16 core dissimilarity measures are introduced and evaluated. We carry out a systematic performance comparison on three image collections, Corel, Getty and Trecvid2003, with 7 different feature spaces. Two search scenarios are considered: single image queries based on the Vector Space Model, and multi-...
متن کاملLearning User Queries in Multimodal Dissimilarity Spaces
Different strategies to learn user semantic queries from dissimilarity representations of video audio-visual content are presented. When dealing with large corpora of videos documents, using a feature representation requires the online computation of distances between all documents and a query. Hence, a dissimilarity representation may be preferred because its offline computation speeds up the ...
متن کاملFuzzy Colour Category Map for Content Based Image Retrieval
In this paper a new colour space for content based image retrieval is presented, which is based upon psychophysical research into human perception. It provides both the ability to measure similarity and determine dissimilarity, using fuzzy logic and psychologically based set theoretic similarity measurement. These properties are shown to be equal or superior to conventional colour spaces. Examp...
متن کامل