TactStyle: Generating Tactile Textures with Generative AI for Digital Fabrication

要旨

Recent work in Generative AI enables the stylization of 3D models based on image prompts. However, these methods do not incorporate tactile information, leading to designs that lack the expected tactile properties. We present TactStyle, a system that allows creators to stylize 3D models with images while incorporating the expected tactile properties. TactStyle accomplishes this using a modified image-generation model fine-tuned to generate heightfields for given surface textures. By optimizing 3D model surfaces to embody a generated texture, TactStyle creates models that match the desired style and replicate the tactile experience. We utilize a large-scale dataset of textures to train our texture generation model. In a psychophysical experiment, we evaluate the tactile qualities of a set of 3D-printed original textures and TactStyle's generated textures. Our results show that TactStyle successfully generates a wide range of tactile features from a single image input, enabling a novel approach to haptic design.

著者
Faraz Faruqi
MIT CSAIL, Cambridge, Massachusetts, United States
Maxine Perroni-Scharf
MIT, Cambridge, Massachusetts, United States
Jaskaran Singh. Walia
Vellore Institute of Technology, Chennai, India
Yunyi Zhu
MIT CSAIL, Cambridge, Massachusetts, United States
Shuyue Feng
Zhejiang University, Hangzhou, China
Donald Degraen
University of Canterbury, Christchurch, New Zealand
Stefanie Mueller
MIT CSAIL, Cambridge, Massachusetts, United States
DOI

10.1145/3706598.3713740

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713740

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Fabrication Techniques

Annex Hall F205
7 件の発表
2025-04-30 23:10:00
2025-05-01 00:40:00
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