Acquisition and Modeling of Non-Rigid Shape and Deformation
Massachusetts Institute Of Technology, Cambridge MA
Investigators
Abstract
Acquisition and Modeling of Non-Rigid Shape and Deformation The acquisition of three-dimensional digital replicas of real-word objects enables digital archiving, virtual restoration, simulation, medicine, education, reverse engineering, and many other applications. The recent success of the efforts to digitize sculptures by Michelangelo, the Florentine Pieta, and artifacts in Cairo's Egyptian Museum demonstrate that the technical challenges involved in scanning static, rigid objects have been largely solved. However, the same scanning technology is far less effective for numerous applications requiring digitization of non-rigid, deforming objects, including humans, animals, and the environment. For example, the state-of-the-art scanners today require human patients to remain motionless in a single pose for several seconds even though infants, small children, and people with disabilities may find it difficult to remain still for the required time periods. More fundamentally, the key drawback of present-day scanning technology is that a single, static scan of a deformable object is a poor representation of its shape because human and animal shapes can easily change at any time instant. This research tackles the algorithmic challenges in acquiring moving three-dimensional shapes. Using high-speed depth cameras to acquire real-time range images allows the object to change freely throughout the scanning process and in the process reveal its entire shape, including the usually occluded regions. The acquired range images are then automatically processed to compute temporal correspondence between data points in nearby frames; to reverse the motion of these data points; and to reconstruct the moving three-dimensional shape in its entirety by aggregating partial information from each time frame. These algorithms simplify acquisition of non-rigid shapes and enable new applications such as studies of locomotion development in humans and animals and content creation for education and training.
View original record on NSF Award Search →