Three-dimensional camera motion estimation with applications to video compression and three-dimensional scene reconstruction

Abstract

In this paper, we propose two classes of algorithms for modeling camera motion in video sequences captured by a camera. The first class can be applied in situations where there is no camera translation and the motion of camera can be adequately modeled by zoom, pan and rotation parameters. The second class is more general in that it can be applied to situations where the camera is undergoing a translational motion, as well as a rotation and zoom and pan. These algorithms are then applied to two problems: predictive video coding and three dimensional ( 3D) scene reconstruction. In predictive coding, the 3D camera motion is estimated from a sequence of frames and used to predict the apparent change in successive frames. In 3D scene reconstruction, a 3D object is "scanned" by translation/rotation motion of the camera along a pre-specified path. The information in successive frames is then used to recover depth at few select locations. The depth and intensity information at these locations are then used to recover the intensity along intermediate points on the scanning path. Experimental results on both these applications will be shown.

Edge-based 3-D camera motion estimation with application to video coding

“…One application of such a scenario might be 3-D video data bases in which 3-D stationary objects are captured on a video sequence by a camera moving around them [37]. In this situation, camera motion estimation techniques can not only be useful for efficient representation of the video sequence, but also for 3-D interpolation of the views not directly captured by the video camera.…”