Pose Metrics: a New Paradigm for Character Motion Edition

TL;DR

This paper introduces pose metrics as a new high-level editing paradigm for character animation, enabling style modifications while maintaining content, balancing control and usability.

Contribution

It proposes pose metrics as a novel objective function framework for animation editing, offering a middle ground between manual data manipulation and semantic style control.

Findings

Pose metrics enable flexible style editing of animations.

The proposed pipeline allows content preservation during style modifications.

This approach improves efficiency and user control in animation editing.

Abstract

In animation, style can be considered as a distinctive layer over the content of a motion, allowing a character to achieve the same gesture in various ways. Editing existing animation to modify the style while keeping the same content is an interesting task, which can facilitate the re-use of animation data and cut down on production time. Existing animation edition methods either work directly on the motion data, providing precise but tedious tools, or manipulate semantic style categories, taking control away from the user. As a middle ground, we propose a new character motion edition paradigm allowing higher-level manipulations without sacrificing controllability. We describe the concept of pose metrics, objective value functions which can be used to edit animation, leaving the style interpretation up to the user. We then propose an edition pipeline to edit animation data using pose metrics.