Every “Body” Gets a Say: An Augmented Optimization Metric to Preserve Body Pose During Avatar Adaptation in Mixed/Augmented Reality

Abstract

User-Avatar interaction within augmented reality applications is rapidly increasing in frequency. Applications routinely place users in rooms with other, remote users embodied by photorealistic avatars, or require users to work with an avatar of a remote user to complete a task. During these types of interactions, it is often required to modify or redirect the posture of an avatar to achieve goals such as contact with or pointing at an object or maintaining eye gaze with the local user. A key limitation of modern redirection techniques is successfully preserving body posture, a critical component of nonverbal communication. This article presents a new pose-preserving objective function to be used in the multi-objective optimization of an avatar's kinematic configuration. This objective function not only mimics the correct placement of body joints, but also preserves their orientation in space. We have tested this approach against several commonly used and current state-of-the-art redirection techniques and have found that our new approach achieves a significant reduction in targeted redirection error while simultaneously reducing body posture error. Additionally, human subject testing has shown that our new technique provides both a significantly more natural looking redirection and a significantly more realistic and believable overall body posture.