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Directional Element HOG for Sketch Recognition

Zhong, Y., Zhang, H., Guo, J. and Song, Yi-Zhe (2018) Directional Element HOG for Sketch Recognition In: 2018 6th International Conference on Network Infrastructure and Digital Content (IC-NIDC 2018), 22-24 Aug 2018, Guiyang, China.

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Abstract

We propose a novel Directional Element Histogram of Oriented Gradient (DE-HOG) feature to human free-hand sketch recognition task that achieves superior performance to traditional HOG feature, originally designed for photographic objects. As a result of modeling the unique characteristics of free-hand sketch, i.e. consisting only a set of strokes omitting visual information such as color and brightness, being highly iconic and abstract. Specifically, we encode sketching strokes as a form of regularized directional vectors from the skeleton of a sketch, whilst still leveraging the HOG feature to meet the local deformation-invariant demands. Such a representation combines the best of two features by encoding necessary and discriminative stroke-level information, but can still robustly deal with various levels of sketching variations. Extensive experiments conducted on two large benchmark sketch recognition datasets demonstrate the performance of our proposed method.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Zhong, Y.
Zhang, H.
Guo, J.
Song, Yi-Zhey.song@surrey.ac.uk
Date : December 2018
DOI : 10.1109/ICNIDC.2018.8525507
Uncontrolled Keywords : Directional element; HOG; Sketch recognition; Stroke-level information
Related URLs :
Additional Information : Printed proceedings are published by Curran Associates Inc., ISBN 9781538660683
Depositing User : Clive Harris
Date Deposited : 02 Jul 2019 09:31
Last Modified : 02 Jul 2019 09:31
URI: http://epubs.surrey.ac.uk/id/eprint/852107

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