Charade: remote control of objects using free-hand gestures
Communications of the ACM - Special issue on computer augmented environments: back to the real world
Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
VIDEOPLACE—an artificial reality
CHI '85 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
“Put-that-there”: Voice and gesture at the graphics interface
SIGGRAPH '80 Proceedings of the 7th annual conference on Computer graphics and interactive techniques
Maximizing the guessability of symbolic input
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Designing the user actions in tangible interaction
Proceedings of the 4th decennial conference on Critical computing: between sense and sensibility
Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters
IEEE Transactions on Computers
User-defined gestures for surface computing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Understanding users' preferences for surface gestures
Proceedings of Graphics Interface 2010
User-defined motion gestures for mobile interaction
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
INTERACT'11 Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction - Volume Part I
User-defined gestures for free-hand TV control
Proceedings of the 10th European conference on Interactive tv and video
Proceedings of the 3rd International Conference on Automotive User Interfaces and Interactive Vehicular Applications
User-defined body gestures for navigational control of a humanoid robot
ICSR'12 Proceedings of the 4th international conference on Social Robotics
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A novel framework is proposed to capture the variability in end user designed gestures and extract archetypal patterns from a pool of gestures sourced from multiple participants. The primary objective is to identify a gesture library that is preferred by the end user population so as to control a human avatar in a 3D virtual environment using whole-of-body gestures. By adapting a group based user centric study, different gesture designs from 36 participants were elicited. Analysis shows that the existing techniques are incapable of extracting archetypal patterns in gestures from such an unconstrained gesture space. As such, a formal notation, followed by hierarchical clustering, is used to provide an abstract representation of gesture designs and then to distil the archetypal gesture patterns from the pool of highly variable gestures. User acceptance of the extracted gestures was performed for validation and common motion patterns were identified from the provided user ratings. The gesture library selected by the framework is compared against the gesture library extracted based on the user ranking, and the similarities and differences between two gesture libraries are presented.