Data-driven finger motion synthesis for gesturing characters
Abstract
Capturing the body movements of actors to create animations for movies, games, and VR applications has become standard practice, but finger motions are usually added manually as a tedious post-processing step. In this paper, we present a surprisingly simple method to automate this step for gesturing and conversing characters. In a controlled environment, we carefully captured and post-processed finger and body motions from multiple actors. To augment the body motions of virtual characters with plausible and detailed finger movements, our method selects finger motion segments from the resulting database taking into account the similarity of the arm motions and the smoothness of consecutive finger motions. We investigate which parts of the arm motion best discriminate gestures with leave-one-out cross-validation and use the result as a metric to select appropriate finger motions. Our approach provides good results for a number of examples with different gesture types and is validated in a perceptual experiment.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Nov 01, 2012
- Source ID
- 10.1145/2366145.2366208
Entities
People
- Alla Safonova
- Jessica Hodgins
- Sophie Jörg
Organizations
- Carnegie Mellon University
- Division of Computing and Communication Foundations
- Division of Information and Intelligent Systems
- Office of Naval Research
- The Walt Disney Company