Optimal multiple sprite generation based on physical camera parameter estimation We present a robust and computational low complex method to estimate the physical camera parameters, intrinsic and extrinsic, for scene shots captured by cameras applying pan, tilt, rotation, and zoom. These parameters are then used to split a sequence of frames into several subsequences in an optimal way to generate multiple sprites. Hereby, optimal means a minimal usage of memory while keeping or even improving the reconstruction quality of the scene background. Since wide angles between two frames of a scene shot cause geometrical distortions using a perspective mapping it is necessary to part the shot into several subsequences. In our approach it is not mandatory that all frames of a subsequence are adjacent frames in the original scene. Furthermore the anglebased classification allows frame reordering and makes our approach very powerful.

GeometryGuided View Synthesis with Local Nonuniform PlaneSweep Volume In this paper we develop a geometryguided image generation technology for sceneindependent novel view synthesis from a stereo image pair. We employ the successful planesweep strategy to tackle the problem of 3D scene structure approximation. But instead of putting on a general configuration, we use depth information to perform a local nonuniform plane spacing. More specifically, we first explicitly estimate a depth map in the reference view and use it to guide the planes spacing in planesweep volume, resulting in a geometryguided manner for scene geometry approximation. Next we learn to predict a multiplane images (MPIs) representation, which can then be used to synthesize a range of novel views of the scene, including views that extrapolate significantly beyond the input baseline, to allow for efficient view synthesis. Our results on massive YouTube video frames dataset indicate that our approach makes it possible to synthesize higher quality images, while keeping the number of depth planes.