Title :
Plane-Based Content Preserving Warps for Video Stabilization
Author :
Zihan Zhou ; Hailin Jin ; Yi Ma
Author_Institution :
Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
Abstract :
Recently, a new image deformation technique called content-preserving warping (CPW) has been successfully employed to produce the state-of-the-art video stabilization results in many challenging cases. The key insight of CPW is that the true image deformation due to viewpoint change can be well approximated by a carefully constructed warp using a set of sparsely constructed 3D points only. However, since CPW solely relies on the tracked feature points to guide the warping, it works poorly in large texture less regions, such as ground and building interiors. To overcome this limitation, in this paper we present a hybrid approach for novel view synthesis, observing that the texture less regions often correspond to large planar surfaces in the scene. Particularly, given a jittery video, we first segment each frame into piecewise planar regions as well as regions labeled as non-planar using Markov random fields. Then, a new warp is computed by estimating a single homography for regions belong to the same plane, while inheriting results from CPW in the non-planar regions. We demonstrate how the segmentation information can be efficiently obtained and seamlessly integrated into the stabilization framework. Experimental results on a variety of real video sequences verify the effectiveness of our method.
Keywords :
Markov processes; deformation; image segmentation; image sequences; random processes; video signal processing; CPW; Markov random fields; building interiors; image deformation technique; jittery video; nonplanar regions; piecewise planar regions; plane-based content preserving warps; segmentation information; sparsely constructed 3D points; textureless regions; tracked feature points; video sequences; video stabilization framework; Cameras; Coplanar waveguides; Image reconstruction; Image segmentation; Motion segmentation; Robustness; Three-dimensional displays;
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
Conference_Location :
Portland, OR
DOI :
10.1109/CVPR.2013.298