Journal Article10.1525/JLIN.1994.4.1.81
Hand and Mind: What Gestures Reveal about Thought
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TL;DR: McNeill as discussed by the authors discusses what Gestures reveal about Thought in Hand and Mind: What Gestures Reveal about Thought. Chicago and London: University of Chicago Press, 1992. 416 pp.
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Abstract: Hand and Mind: What Gestures Reveal about Thought. David McNeill. Chicago and London: University of Chicago Press, 1992. 416 pp.
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References
How to Click in Mid-Air
Florian van de Camp,Alexander Schick,Rainer Stiefelhagen +2 more
- 21 Jul 2013
TL;DR: This paper investigates interactions with distant interfaces and proposes a taxonomy for distant one-arm clicking gestures and identifies groups of gestures of varying acceptability that can serve as a reference for interface designers to select the most suitable gesture.
Computational Characteristics of Multimodal Dialogue
Kris R. Thrisson
- 01 Jan 1998
TL;DR: A layered feedback-loop model of face-to-face dialogue is presented and it is shown how contextual analysis of the function of multimodal acts is linked with feedback generation and interpretation.
The interactional geometry of a three-way conversation
Patrick G. T. Healey,Stuart A. Battersby +1 more
- 01 Jan 2009
TL;DR: Healey et al. as discussed by the authors describe patterns of spatial co-ordination that, in part, are a distinctive characteristic of multi-person face-to-face interactions and show that participants make frequent use of combi- nations of head angle, gesture and participants' positions to triangulate their contributions.
A survey of 2D and 3D imaging used in hand gesture recognition for human-computer interaction (HCI)
Rajeshri R. Itkarkar,Anilkumar V. Nandi +1 more
- 01 Dec 2016
TL;DR: The study of the techniques applied for recognizing gesture in real time application is presented and on various techniques and the conditions under which the methodologies are employed.
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Speaker movement correlates with prosodic indicators of engagement
TL;DR: In this paper, the authors introduce movement amplitude, a new vision-based metric for estimating continuous body movements over time from video by quantifying frameto-frame visual changes and demonstrate that speakers move more during phrases in which their pitch and intensity are higher and more variable.