Video Completion for Perspective Camera Under Constrained Motion

This paper presents a novel technique to fill in missing background and moving foreground of a video captured by a static or moving camera. Different from previous efforts which are typically based on processing in the 3D data volume, we slice the volume along the motion manifold of the moving object, and therefore reduce the search space from 3D to 2D, while still preserve the spatial and temporal coherence. In addition to the computational efficiency, based on geometric video analysis, the proposed approach is also able to handle real videos under perspective distortion, as well as common camera motions, such as panning, tilting, and zooming. The experimental results demonstrate that our algorithm performs comparably to 3D search based methods, and however extends the current state-of-the-art repairing techniques to videos with projective effects, as well as illumination changes

[1]  W. Eric L. Grimson,et al.  Learning Patterns of Activity Using Real-Time Tracking , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Dorin Comaniciu,et al.  Real-time tracking of non-rigid objects using mean shift , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[3]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[4]  Guillermo Sapiro,et al.  Navier-stokes, fluid dynamics, and image and video inpainting , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[5]  Ramakant Nevatia,et al.  Self-calibration of a camera from video of a walking human , 2002, Object recognition supported by user interaction for service robots.

[6]  Tai-Pang Wu,et al.  Video repairing: inference of foreground and background under severe occlusion , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[7]  Patrick Pérez,et al.  Region filling and object removal by exemplar-based image inpainting , 2004, IEEE Transactions on Image Processing.

[8]  Eli Shechtman,et al.  Space-time video completion , 2004, CVPR 2004.

[9]  Ralph R. Martin,et al.  Video completion using tracking and fragment merging , 2005, The Visual Computer.

[10]  Denis Simakov,et al.  Space-time scene manifolds , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[11]  Guillermo Sapiro,et al.  Video inpainting of occluding and occluded objects , 2005, IEEE International Conference on Image Processing 2005.

[12]  Harry Shum,et al.  Image completion with structure propagation , 2005, ACM Trans. Graph..

[13]  Mubarak Shah,et al.  Motion Layer Based Object Removal in Videos , 2005, 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1.

[14]  Harry Shum,et al.  Full-frame video stabilization , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[15]  Wu Zhong International Trends of Pattern Recognition Research A Brief Introduction to the 18th International Conference on Pattern Recognition , 2006 .