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Freehand sketches are an interesting universal form of visual representation. Sketching has become easily accessible with many of the devices that we use on a daily basis. In this paper, we propose a system for real-time sketch recognition and similarity search. Our system is able to recognize partial sketches from 250 object categories. It is then able to retrieve similar sketches but also images/photographs. In this work, we propose to use deep convolutional neural networks (ConvNets) for partial sketch recognition and feature extraction. Features are extracted from sketches and image contours in order to be used as a basis for similarity search using k-Nearest Neighbors (kNN). Our system demonstrates promising results in identifying similar images, and could be integrated in larger content-based search engines.
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Omar Seddati
University of Mons
Stéphane Dupont
Australian National University
Saïd Mahmoudi
International Life Sciences Institute Europe
University of Mons
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Seddati et al. (Thu,) studied this question.
synapsesocial.com/papers/6a12d61706ed52b5c2c0a142 — DOI: https://doi.org/10.1145/2964284.2973828