A methodology to establish ground truth for computer vision algorithms to estimate haptic features from visual images

Abstract

Humans have an uncanny ability to estimate haptic features of an object such as haptic shape, size, texture and material by visual inspection. A significant computer vision problem is that of estimating haptic features from visual images. While explorations have been made in estimation of visual features such as visual texture, work on estimation of haptic features from video is still in its infancy. We present a methodology to establish ground truth for estimation of haptic features from visual images. We assembled a visio-haptic database of 48 objects ranging from nonsense objects to everyday objects. The variation was controlled in objects by systematically varying haptic features such as shape and texture, and the physical and perceptual ground truth of visual and haptic features was documented. This database provides visio-haptic features of objects and can be used to develop algorithms to estimate haptic features from visual images. Finally, a tactile cueing experiment is presented demonstrating how visio-haptic ground truth can be used to assess the accuracy of a system for visio-haptic conversion of image content.