  Finger-tip tactile sensors are increasingly used for robotic sensing to
establish stable grasps and to infer object properties. Promising performance
has been shown in a number of works for inferring adjectives that describe the
object, but there remains a question about how each taxel contributes to the
performance. This paper explores this question with empirical experiments,
leading insights for future finger-tip tactile sensor usage and design.
