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A New Approach to Automatic Clothing Matting from Mannequins

Yuan, B; Lu, Z; Xue, J-H; Liao, Q; (2019) A New Approach to Automatic Clothing Matting from Mannequins. In: Karam, Lina J and Mei, Tao and Wu, Feng, (eds.) Proceedings of the IEEE International Conference on Multimedia and Expo (ICME) 2019. IEEE: New York, USA. Green open access

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Abstract

It is crucial to extract retail clothes from images of mannequins when building a database of clothing images for virtual try-on systems. However, clothes often have complex texture and translucent material, such as holes and laces. It is thus difficult to extract clothes as foreground by existing generic natural image matting methods. Hence in this paper, we present a novel approach to automatic clothing matting from mannequins, with auxiliary information from a rough background image of the mannequin only. Experiments show that we can achieve remarkable improvement on the alpha matte near challenging regions of complex texture and translucent material of clothes. Moreover, our approach can automatically generate trimaps to facilitate the development and evaluation of other image matting algorithms.

Type: Proceedings paper
Title: A New Approach to Automatic Clothing Matting from Mannequins
ISBN-13: 978-1-5386-9552-4
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/icme.2019.00156
Publisher version: https://doi.org/10.1109/ICME.2019.00156
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Clothing, Image color analysis, Databases, Buildings, Memory management, Bayes methods, Measurement, Clothing image matting, Virtual clothing try-on
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10079664
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