Online Avatar Motion Adaptation to Morphologically-similar Spaces

Abstract

In avatar-mediated telepresence systems, a similar environment is assumed for involved spaces, so that the avatar in a remotespace can imitate the user’s motion with proper semantic intention performed in a local space. For example, touching on thedesk by the user should be reproduced by the avatar in the remote space to correctly convey the intended meaning. It is unlikely,however, that the two involved physical spaces are exactly the same in terms of the size of the room or the locations of the placedobjects. Therefore, a naive mapping of the user’s joint motion to the avatar will not create the semantically correct motion of theavatar in relation to the remote environment. Existing studies have addressed the problem of retargeting human motions to anavatar for telepresence applications. Few studies, however, have focused on retargeting continuous full-body motions such aslocomotion and object interaction motions in a unified manner. In this paper, we propose a novel motion adaptation method thatallows to generate the full-body motions of a human-like avatar on-the-fly in the remote space. The proposed method handleslocomotion and object interaction motions as well as smooth transitions between them according to given user actions under thecondition of a bijective environment mapping between morphologically-similar spaces. Our experiments show the effectivenessof the proposed method in generating plausible and semantically correct full-body motions of an avatar in room-scale space.