A visuo-tactile deep network using a CNN autoencoder and ConvLSTM predicts four haptic attribute ratings from images and tool vibrations, beating single-modality baselines in leave-one-out tests.
Modeling and render- ing realistic textures from unconstrained tool-surface interactions,
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Estimating Perceptual Attributes of Haptic Textures Using Visuo-Tactile Data
A visuo-tactile deep network using a CNN autoencoder and ConvLSTM predicts four haptic attribute ratings from images and tool vibrations, beating single-modality baselines in leave-one-out tests.