Modeling context in haptic perception, rendering and visualization

Authors:
Kanav Kahol;Priyamvada Tripathi;Troy McDaniel;Sethuraman Panchanathan
Affiliations:
Center for Cognitive Ubiquitous Computing, Department of Computer Science and Engineering, Arizona State University, Tempe, Arizona;Center for Cognitive Ubiquitous Computing, Department of Computer Science and Engineering, Arizona State University, Tempe, Arizona;Center for Cognitive Ubiquitous Computing, Department of Computer Science and Engineering, Arizona State University, Tempe, Arizona;Center for Cognitive Ubiquitous Computing, Department of Computer Science and Engineering, Arizona State University, Tempe, Arizona
Venue:
MIS'05 Proceedings of the 11th international conference on Advances in Multimedia Information Systems
Year:
2005

Citing 2
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Modeling context in haptic perception, rendering, and visualization

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)

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Abstract

Haptic perception refers to the human ability to perceive spatial properties through tactile and haptic sensations. Humans have an uncanny ability to analyze objects based only on sparse information from haptic stimuli. Contextual clues about material of an object, its overall shape, size and weight configurations perceived by individuals, lead to recognition of an object and its spatial features. In this paper, we present strategies and algorithms to model context in haptic applications that allow user to explore objects in virtual reality/augmented reality, haptically. Our methodology is based on modeling user's cognitive and motor strategy of haptic exploration. Additionally we also model physiological arrangement of tactile sensors in the human hand. These models provide the context to adapt haptic displays to a user's style of haptic perception and exploration and the present state of the user's exploration. We designed a tactile cueing paradigm to test the validity of the contextual models. Initial results show improvement in accuracy and efficiency of haptic perception when compared to the conventional approaches that do not model context in haptic rendering.