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Towards the design of effective freehand gestural interaction for interactive TV

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Title: Towards the design of effective freehand gestural interaction for interactive TV
Authors: Ren, G
Li, W
O’Neill, E
Item Type: Journal Article
Abstract: As interactive devices become pervasive, people are beginning to look for more advanced interaction with televisions in the living room. Interactive television has the potential to offer a very engaging experience. But most common user tasks are still challenging with such systems, such as menu selection or text input, and little work has been done on understanding and supporting the effective design of freehand interaction with a TV in the domestic environment. In this paper, we report two studies investigating freehand gestural interaction with a consumer level sensor that is suitable for TV use scenarios. In the first study, we investigate a range of design factors for tiled layout menu selection, including wearable feedback, push gesture depth, target size and position in motor space. The results show that tactile and audio feedback have no significant effect on user performance and preference, and these results inform potential designs for high selection performance. In the second study, we investigate using freehand gestures for the common TV user task of text input. We design and evaluate two virtual keyboard layouts and three freehand selection methods. Results show that ease of use and error tolerance can both be achieved using a text entry method utilizing a dual circle layout and an expanding target selection technique. Finally, we propose design guidelines for effective, usable and comfortable freehand gestural interaction for interactive TV based on the findings.
Editors: Lv, Z
Issue Date: 13-Oct-2016
Date of Acceptance: 1-Oct-2016
URI: http://hdl.handle.net/10044/1/53890
DOI: https://dx.doi.org/10.3233/JIFS-169106
ISSN: 1064-1246
Publisher: IOS Press
Start Page: 2659
End Page: 2674
Journal / Book Title: Journal of Intelligent and Fuzzy Systems
Volume: 31
Issue: 5
Copyright Statement: © 2016 – IOS Press and the authors. All rights reserved
Keywords: cs.HC
0801 Artificial Intelligence And Image Processing
1702 Cognitive Science
Artificial Intelligence & Image Processing
Publication Status: Published
Appears in Collections:Computing
Faculty of Engineering