- About CSAIL
- News + Events
- Alumni & Friends
Graphics and Vision
Deformation Transfer for Triangle Meshes
Deformation transfer applies the deformation exhibited by a source triangle mesh onto a different target triangle mesh. Our approach is general and does not require the source and target to share the same number of vertices or triangles, or to have identical connectivity. The user builds a correspondence map between the triangles of the source and those of the target by specifying a small set of vertex markers. Deformation transfer computes the set of transformations induced by the deformation of the source mesh, maps the transformations through the correspondence from the source to the target, and solves an optimization problem to consistently apply the transformations to the target shape.
This paper describes a method for bringing two videos (recorded at different times) into spatiotemporal alignment, then comparing and combining corresponding pixels for applications such as background subtraction, compositing, and increasing dynamic range. We align a pair of videos by searching for frames that best match according to a robust image registration process. This process uses locally weighted regression to interpolate and extrapolate high-likelihood image correspondences, allowing new correspondences to be discovered and refined. Image regions that cannot be matched are detected and ignored, providing robustness to changes in scene content and lighting, which allows a variety of new applications.
Adaptation of Performed Ballistic Motion
Adaptation of ballistic motion demands a technique that can make required adjustments in anticipation of flight periods when only some physically consistent changes are possible. This article describes a numerical procedure that adjusts a physically consistent motion to fulfill new adaptation requirements expressed in kinematic and dynamic constraints. This iterative procedure refines the original motion with a sequence of minimal adjustments, implicitly favoring motions that are similar to the original performance, and transforming any input motion, including those that are difficult to characterize with an objective function.