3D tracking for gait characterization and recognition

We propose an approach to gait analysis that relies on fitting 3D temporal motion models to synchronized video sequences. These models allow us not only to track but also to recover motion parameters that can be used to recognize people and characterize their style. Because our method is robust to occlusions and insensitive to changes in direction of motion, our proposed approach has the potential to overcome some of the main limitations of current gait analysis methods. This is an important step towards taking biometrics out of the laboratory and into the real world.