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.