3D lip shapes from video: A combined physical-statistical model

Tracking human lips in video is an important but notoriously dicult task. To accurately recover their motions in 3D from any head pose is an even more challenging task, though still necessary for natural interactions. Our approach is to build and train 3D models of lip motion to make up for the information we cannot always observe when tracking. We use physical models as a prior and combine them with statistical models, showing how the two can be smoothly and naturally integrated into a synthesis method and a MAP estimation framework for tracking. We have found that this approach allows us to accurately and robustly track and synthesize the 3D shape of the lips from arbitrary head poses in a 2D video stream. We demonstrate this with numerical results on reconstruction accuracy, examples of static ®ts, and audio-visual sequences. Ó 1998 Elsevier Science B.V. All rights reserved.

• Type: Journal
• Year: 1998
• Where: SPEECH
• Authors: Sumit Basu, Nuria Oliver, Alex Pentland
• Keywords: Dicult Task, Human Lips, MAP Estimation Framework, SPEECH 1998