An annotation scheme for conversational gestures: how to economically capture timing and form

The empirical investigation of human gesture stands at the center of multiple research disciplines, and various gesture annotation schemes exist, with varying degrees of precision and annotation effort. We present a gesture annotation scheme for the specific purpose of automatically generating and animating character-specific hand/arm gestures, but with potential general value. We focus on how to capture temporal structure and locational information with relatively little annotation effort. The scheme is evaluated in terms of how accurately it captures the original gestures by re-creating those gestures on an animated character using the annotated data. This paper presents our scheme in detail and compares it to other approaches. Author