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Sketch-based interaction and modeling: where do we stand?

Bonnici, Alexandra, Akman, Alican, Calleja, Gabriel, Camilleri, Kenneth P., Fehling, Patrick, Ferreira, Alfredo, Hermuth, Florian, Israel, Johann Habakuk, Landwehr, Tom, Liu, Juncheng, Padfield, Natasha M. J., Sezgin, T. Metin and Rosin, Paul L. 2019. Sketch-based interaction and modeling: where do we stand? AI EDAM 33 (4) , pp. 370-388. 10.1017/S0890060419000349

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Abstract

Sketching is a natural and intuitive communication tool used for expressing concepts or ideas which are difficult to communicate through text or speech alone. Sketching is therefore used for a variety of purposes, from the expression of ideas on two-dimensional (2D) physical media, to object creation, manipulation, or deformation in three-dimensional (3D) immersive environments. This variety in sketching activities brings about a range of technologies which, while having similar scope, namely that of recording and interpreting the sketch gesture to effect some interaction, adopt different interpretation approaches according to the environment in which the sketch is drawn. In fields such as product design, sketches are drawn at various stages of the design process, and therefore, designers would benefit from sketch interpretation technologies which support these differing interactions. However, research typically focuses on one aspect of sketch interpretation and modeling such that literature on available technologies is fragmented and dispersed. In this paper, we bring together the relevant literature describing technologies which can support the product design industry, namely technologies which support the interpretation of sketches drawn on 2D media, sketch-based search interactions, as well as sketch gestures drawn in 3D media. This paper, therefore, gives a holistic view of the algorithmic support that can be provided in the design process. In so doing, we highlight the research gaps and future research directions required to provide full sketch-based interaction support.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Cambridge University Press (CUP)
ISSN: 0890-0604
Date of First Compliant Deposit: 1 April 2020
Date of Acceptance: 25 October 2019
Last Modified: 29 May 2020 02:05
URI: http://orca.cf.ac.uk/id/eprint/130683

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