LAUSR

We present a hybrid framework for the modeling and rendering of both homogeneous and inhomogeneous textures with high realism by combining force and vibration feedback. Given a real texture sample, we first capture a force-feedback model using photometric stereo, which is one of the most accurate algorithms for 3D surface reconstruction in computer vision. This method allows us to model the micro-geometry of the surface and represent it by a two-dimensional (2D) height map in a very high resolution to the order of 10 $\mu \text{m}$ . We also provide a new force rendering algorithm adequate for such an accurate and fine texture model. By a user study, we verify that the proposed force modeling and rendering algorithms are suitable for our hybrid texture framework. Second, we model the homogeneous and stationary vibrational characteristics of the real texture sample using the prevalent LPC (linear predictive coding)-based method. Third, we merge the force and vibration feedback models appropriately into a hybrid framework on the basis of their spectral characteristics. Last, another user study that assessed the perceived similarity between real textures and their virtual simulations demonstrates that our hybrid framework can achieve a high level of realism. To our knowledge, our framework is unique in that it can model inhomogeneous (in additional to homogeneous) real textures and render them in a virtual environment with high realism by providing both force and vibrational sensory cues.