Title: Tracking Articulated Objects with a High-Resolution Deformable Surface Model
Advisors: Dieter Fox and Brian Curless
Abstract: The last several years have seen significant progress in using depth cameras for tracking articulated objects such as human bodies, hands, or robotic manipulators. Most approaches focus on tracking skeletal parameters of a fixed shape model, which makes them insufficient for robotics applications that require accurate estimates of object surfaces. To overcome this limitation, we present a 3D model-based tracking system for articulated deformable objects. Our system is able to track human body pose and high resolution surface contours in real time using a commodity depth sensor and GPU hardware. We implement this as a joint optimization over a skeleton to account for changes in pose, and over the vertices of a high resolution mesh to track the subject's shape. With this model we are able to capture dynamic sub-centimeter surface detail such as face deformations and folds and wrinkles in clothing. The end result is highly accurate spatiotemporal and semantic information which is well suited for physical human robot interaction.