Perceptually Lossless Tactile Texture Synthesis with Compact Spectral Envelope Models

2026-05-22

AI Summary

This work addresses the challenge that existing tactile signal representations rely on high-resolution data, which is difficult to compress or generate efficiently. To overcome this limitation, the authors propose two perceptually driven, compact spectral envelope models: spectral beta, based on the Beta distribution, and spectral slope, derived from asymmetric bandpass filters. By modeling only the fundamental structure of the time–frequency spectrogram, these approaches preserve critical perceptual information. In experiments with 14 participants, tactile textures synthesized using spectral beta achieved realism ratings comparable to high-fidelity playback. Regression analysis further revealed that energy alignment across nine critical bands is the strongest predictor of perceived authenticity. This study represents the first successful application of compact spectral models to tactile texture synthesis, enabling perceptually lossless rendering.

Abstract

Modern audio-visual media rely on compact representations for efficient storage and transmission, whereas realistic digital touch still depends on high-resolution tactile recordings. Existing approaches for representing tactile signals constrain manipulation and limit the generation of new content. Here, we introduce two compact representations, spectral beta and spectral slope, that capture the temporal spectral structure of finger-surface friction signals while preserving perceptually relevant information. Spectral beta models spectral skewness using a two-parameter beta distribution, whereas spectral slope approximates the spectrum with an asymmetric bandpass filter defined by low- and high-pass orders. We evaluated these representations in a perceptual study with 14 participants using five virtual textures rendered on a friction-modulation display and compared them with physical textures and high-fidelity reproductions of recorded signals. Spectral beta achieved perceptual similarity ratings comparable to those of the original high-fidelity reproductions. Regression analysis further showed that matching spectral energy across nine critical frequency bands was the strongest predictor of perceived realism. Together, these findings suggest that tactile texture perception depends primarily on fundamental temporal spectral patterns and that modeling these patterns is sufficient for perceptually realistic rendering. These results establish an efficient and scalable framework for haptic compression, communication, and synthetic texture generation.

Problem

• tactile texture
• compact representation
• perceptual realism
• haptic compression
• spectral modeling

Innovation

• spectral beta
• spectral slope
• perceptually lossless
• tactile texture synthesis
• haptic compression