A robust subspace approach to extracting layers from image sequences
Qifa Ke, Takeo Kanade · 2003
The views and conclusions contained in this document are those of the author and should not be interpreted as representing the official policies, either expressed or implied, of the Carnegie Mellon University or the U.S. Government or any of its agency. Keywords: layer extraction, layered representation, subspace, clustering, robust, A layer is a 2D sub-image inside which pixels share common apparent motion of some 3D scene plane. Representing videos with such layers has many important applications, such as video compression, 3D scene and motion analysis, object detection and tracking, and vehicle navigation. Extracting layers from videos involves solving three subproblems: 1) segment the image into sub-regions (layers); 2) estimate the 2D motion of each layer; and 3) determine the number of layers. These three subproblems are highly intertwined, making the layer extraction problem very challenging. Existing approaches to layer extraction are limited by 1) requiring good initial segmentation, 2) strong assumptions about the scene, 3) unable to fully and simultaneously utilize the spatial and temporal