A descriptor for large scale image retrieval based on sketched feature lines
Mathias Eitz, Kristian Hildebrand, Tamy Boubekeur, and Marc Alexa Eurographics SBIM 2009
Left: user sketches used as input for the search engine. Right: queries results
Abstract
We address the problem of large scale sketch based image retrieval, searching in a database of over a million images. The search is based on a descriptor that elegantly addresses the asymmetry between the binary user sketch on the one hand and the full color image on the other hand. The proposed descriptor is constructed such that both the full color image and the sketch undergo exactly the same preprocessing steps. We also design an adapted version of the descriptor proposed for MPEG-7 and compare their performance on a database of 1.5 million images. Best matching images are clustered based on color histograms, to offset the lacking color in the query. Overall, the query results demonstrate that the system allows users an intuitive access to large image databases.
Paper
Full Res.
Low Res.
BibTex Reference @InProceedings{Eitz:2009:SBIR,
author = {Mathias Eitz, Kristian Hildebrand, Tamy Boubekeur and Marc Alexa},
title = {A descriptor for large scale image retrieval based on sketched feature lines},
booktitle ={Eurographics Symposium on Sketch-Based Interfaces and Modeling},
year = {2009}
pages = {29--38}
}
