A review of computable expressive descriptors of human motion

Abstract

In this paper we present a review of computable descriptors of human motion. We first present low-level descriptors that compute quantities directly from the raw motion data. We then present higher level descriptors that use low-level ones to compute boolean, single value or continuous quantities that can be interpreted, automatically or manually, to qualify the meaning, style or expressiveness of a motion. We provide formulas inspired from the state of the art that can be applied to 3D motion capture data.