|An example of a human video texture generated from 6 separate sets of motion capture data and video. The transition frames are shown clearly while the others are faded out for clarity. Colors correspond to specific clips which are interleaved between transitions.|
*School of Interactive Computing
Georgia Institute of Technology
|Sing Bing Kang
|Young Kee Ryu
|Irfan Essa*||James M. Rehg*|
This paper describes a data-driven approach for generating photorealistic animations of human motion. Each animation sequence follows a user-choreographed path and plays continuously by seamlessly transitioning between different segments of the captured data. To produce these animations, we capitalize on the complementary characteristics of motion capture data and video. We customize our capture system to record motion capture data that are synchronized with our video source. Candidate transition points in video clips are identified using a new similarity metric based on 3-D marker trajectories and their 2-D projections into video. Once the transitions have been identified, a video-based motion graph is constructed. We further exploit hybrid motion and video data to ensure that the transitions are seamless when generating animations. Motion capture marker projections serve as control points for segmentation of layers and nonrigid transformation of regions. This allows warping and blending to generate seamless in-between frames for animation. We show a series of choreographed animations of walks and martial arts scenes as validation of our approach.
Publicationdownload pre-print publication (24 MB pdf):
Matthew Flagg, Atsushi Nakazawa, Qiushuang Zhang, Sing Bing Kang,
Young Kee Ryu, Irfan Essa and James M. Rehg. Human video textures.
In SI3D ’09: Proceedings of the 2009 Symposium on Interactive
3D Graphics and Games, ACM, New York, NY, USA.
Videodownload I3D video submission (74 MB) - download DivX player here