Interpretation of Tactile Sensation using an Anthropomorphic Finger Motion Interface to Operate a Virtual Avatar
February 20, 2019 Β· Declared Dead Β· π ICAT-EGVE
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Yusuke Ujitoko, Koichi Hirota
arXiv ID
1902.07403
Category
cs.HC: Human-Computer Interaction
Citations
5
Venue
ICAT-EGVE
Last Checked
4 months ago
Abstract
The objective of the system presented in this paper is to give users tactile feedback while walking in a virtual world through an anthropomorphic finger motion interface. We determined that the synchrony between the first person perspective and proprioceptive information together with the motor activity of the user's fingers are able to induce an illusionary feeling that is equivalent to the sense of ownership of the invisible avatar's legs. Under this condition, the perception of the ground under the virtual avatar's foot is felt through the user's fingertip. The experiments indicated that using our method the scale of the tactile perception of the texture roughness was extended and that the enlargement ratio was proportional to the avatar's body (foot) size. In order to display the target tactile perception to the users, we have to control only the virtual avatar's body (foot) size and the roughness of the tactile texture. Our results suggest that in terms of tactile perception fingers can be a replacement for legs in locomotion interfaces.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted