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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - Tactile Mesh Saliency
T2 - a brief synopsis
AU - Lau, Manfred Chung Man
AU - Dev, Kapil
PY - 2016/9/15
Y1 - 2016/9/15
N2 - This work has previously been published [LDS 16] and this extended abstract provides a synopsis for further discussion at the UK CGVC 2016 conference. We introduce the concept of tactile mesh saliency, where tactile salient points on a virtual mesh are those that a human is more likely to grasp, press, or touch if the mesh were a real-world object. We solve the problem of taking as input a 3D mesh and computing the tactile saliency of every mesh vertex. The key to solving this problem is in a new formulation that combines deep learning and learning-to-rank methods to compute a tactile saliency measure. Finally, we discuss possibilities for future work.
AB - This work has previously been published [LDS 16] and this extended abstract provides a synopsis for further discussion at the UK CGVC 2016 conference. We introduce the concept of tactile mesh saliency, where tactile salient points on a virtual mesh are those that a human is more likely to grasp, press, or touch if the mesh were a real-world object. We solve the problem of taking as input a 3D mesh and computing the tactile saliency of every mesh vertex. The key to solving this problem is in a new formulation that combines deep learning and learning-to-rank methods to compute a tactile saliency measure. Finally, we discuss possibilities for future work.
U2 - 10.2312/cgvc.20161302
DO - 10.2312/cgvc.20161302
M3 - Conference contribution/Paper
SN - 9783038680222
BT - Computer Graphics and Visual Computing (CGVC)
A2 - Turkay, Cagatay
A2 - Wan, Tao Ruan
PB - The Eurographics Association
ER -