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Im2Sketch: Sketch generation by unconflicted perceptual grouping

Qi, Y., Guo, J., Song, Yi-Zhe, Xiang, T., Zhang, H. and Tan, Z.-H. (2015) Im2Sketch: Sketch generation by unconflicted perceptual grouping Neurocomputing, 165. pp. 338-349.

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Abstract

Effectively solving the problem of sketch generation, which aims to produce human-drawing-like sketches from real photographs, opens the door for many vision applications such as sketch-based image retrieval and non-photorealistic rendering. In this paper, we approach automatic sketch generation from a human visual perception perspective. Instead of gathering insights from photographs, for the first time, we extract information from a large pool of human sketches. In particular, we study how multiple Gestalt rules can be encapsulated into a unified perceptual grouping framework for sketch generation. We further show that by solving the problem of Gestalt confliction, i.e., encoding the relative importance of each rule, more similar to human-made sketches can be generated. For that, we release a manually labeled sketch dataset of 96 object categories and 7680 sketches. A novel evaluation framework is proposed to quantify human likeness of machine-generated sketches by examining how well they can be classified using models trained from human data. Finally, we demonstrate the superiority of our sketches under the practical application of sketch-based image retrieval. © 2015 Elsevier B.V.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Qi, Y.
Guo, J.
Song, Yi-Zhey.song@surrey.ac.uk
Xiang, T.
Zhang, H.
Tan, Z.-H.
Date : 1 October 2015
DOI : 10.1016/j.neucom.2015.03.023
Uncontrolled Keywords : Gestalt confliction; Perceptual grouping; RankSVM; Sketch generation; Sketch-based image retrieval
Depositing User : Clive Harris
Date Deposited : 23 Jul 2019 13:33
Last Modified : 23 Jul 2019 13:33
URI: http://epubs.surrey.ac.uk/id/eprint/852135

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