User-defined gestures for augmented reality

By Thammathip Piumsomboon, Adrian Clark, Mark Billinghurst, A. Cockburn. IFIP TC13 International Conference on Human-Computer Interaction, 2013

383 citations recorded by the source corpus.

Recently there has been an increase in research of hand gestures for interaction in the area of Augmented Reality (AR). However this research has focused on developer designed gestures, and little is known about user preference and behavior for gestures in AR. In this paper, we present the results of a guessability study focused on hand gestures in AR. A total of 800 gestures have been elicited for 40 selected tasks from 20 partic-ipants. Using the agreement found among gestures, a user-defined gesture set was created to guide design-ers to achieve consistent user-centered gestures in AR.

Subfields: Computer Vision and Pattern Recognition, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/c3f7108476207c77a9a257eca14278ad9d749b6c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Yan Zhang
2. Philip H. S. Torr
3. Rodrigo de Bem
4. Adnane Boukhayma
5. Cordelia Schmid
6. Luc Van Gool
7. Ivan Laptev
8. Ming-Hsuan Yang

In Human-Computer Interaction

1. Philip H. S. Torr
2. Rodrigo de Bem
3. Adnane Boukhayma
4. Gyeongsik Moon
5. Kyoung Mu Lee

Citations in the corpus

• Mobile Edge Computing: A Survey (2018, background): “AR enables real environment user experience by combining real and virtual objects existing simultaneously [40], [41].”
• 3D Hand Shape and Pose From Images in the Wild (2019, background): “Human hand pose estimation and reconstruction in 3D is a long standing problem in the computer vision and graphics communities that has applications in various domains such as virtual and augmented reality and humanmachine interaction [35, 15, 46, 13].”