Deformable Models for Segmentation, 3D Shape and Motion Estimation and Recognition

We present our framework for segmentation, 3D shape and motion estimation and recognition. We first present physics-based modeling techniques for segmentation and 3D shape and motion estimation based on single and multiple views as well as the integration of visual cues such as edges and optical flow. We then present extensions to address the reliable recognition of American Sign Language (ASL), using 3D tracking data, ASL phonology and modifications to the traditional use of Hidden Markov Models. We demonstrate the usefulness of this framework in computer vision and medical image analysis applications