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arXiv · 2601.16639

HapticMatch: An Exploration for Generative Material Haptic Simulation and Interaction

Mingxin Zhang·Yu Yao·Yasutoshi Makino·Hiroyuki Shinoda·Masashi Sugiyama
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Abstract

High-fidelity haptic feedback is essential for immersive virtual environments, yet authoring realistic tactile textures remains a significant bottleneck for designers. We introduce HapticMatch, a visual-to-tactile generation framework designed to democratize haptic content creation. We present a novel dataset containing precisely aligned pairs of micro-scale optical images, surface height maps, and friction-induced vibrations for 100 diverse materials. Leveraging this data, we explore and demonstrate that conditional generative models like diffusion and flow-matching can synthesize high-fidelity, renderable surface geometries directly from standard RGB photos. By enabling a "Scan-to-Touch" workflow, HapticMatch allows interaction designers to rapidly prototype multimodal surface sensations without specialized recording equipment, bridging the gap between visual and tactile immersion in VR/AR interfaces.

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Mingxin Zhang, Yu Yao, Yasutoshi Makino, Hiroyuki Shinoda, Masashi Sugiyama. 2026-01-23. HapticMatch: An Exploration for Generative Material Haptic Simulation and Interaction. https://arxiv.org/abs/2601.16639

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