“Image retrieval using collaborative filtering and visual navigation” by Barthel, Muller, Backstein, Neumann and Jung
Conference:
Type:
Entry Number: 87
Title:
- Image retrieval using collaborative filtering and visual navigation
Presenter(s)/Author(s):
Abstract:
Internet image search systems mostly use words from the context of the web page containing the image as keywords. The performance of these search systems is rather poor, as the search systems neither know the intention of the searching user nor the semantic relationships of these images. Content-based image retrieval (CBIR) systems rely on the assumption that similar images share similar visual features. Despite intense research efforts, the results of CBIR systems have not reached the performance of text based search engines. The main problem of CBIR systems is the semantic gap between the content that can be described with low-level visual features and the description of image content that humans use with high-level semantic concepts. Some image retrieval systems have combined the keyword and the content-based visual search approach. However with this approach many images may be found that semantically do not match. In addition semantically similar images that visually look different cannot be found at all.
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