Visual hull construction, alignment and refinement for human kinematic modeling, motion tracking and rendering

• Authors: Kong Man (German) Cheung;Takeo Kanade;Simon Baker
• Venue: Visual hull construction, alignment and refinement for human kinematic modeling, motion tracking and rendering
• Year: 2003

The abilities to build precise human kinematic models and to perform accurate human motion tracking are essential in a wide variety of applications. Due to the complexity of the human bodies and the problem of self-occlusion, modeling and tracking humans using cameras are challenging tasks. In this thesis, we develop algorithms to perform these two tasks based on the shape estimation method Shape-From-Silhouette (SFS) which constructs a shape estimate (known as Visual Hull) of an object using its silhouettes images. In the first half of this thesis we extend the traditional SFS algorithm so that it can be used effectively for the human related applications. To perform SFS in real-time, we propose a fast testing/projection algorithm for voxel-based SFS algorithms. Moreover, we combine silhouette information over time to effectively increase the number of cameras (and hence reconstruction details) for SFS without physically adding new cameras. We first propose a new Visual Hull representation called Bounding Edges. We then analyze the ambiguity problem of aligning two Visual Hulls. Based on the analysis, we develop an algorithm to align Visual Hulls over time using stereo and an important property of the Shape-From-Silhouette principle. This temporal SFS algorithm combines both geometric constraints and photometric consistency to align Colored Surface Points of the object extracted from the silhouette and color images. Once the Visual Hulls are aligned, they are refined by compensating for the motion of the object. The algorithm is developed for both rigid and articulated objects. In the second half of this thesis we show how the improved SFS algorithms are used to perform the tasks of human modeling and motion tracking. First we build a system to acquire human kinematic models consisting of precise shape and joint locations. Once the kinematic models are built, they are used to track the motion of the person in new video sequences. The tracking algorithm is based on the Visual Hull alignment idea used in the temporal SFS algorithms. Finally we demonstrate how the kinematic model and the tracked motion data can be used for image-based rendering and motion transfer between two people.