| Paper ID | IVMSP-15.5 |
| Paper Title |
EFFICIENT REAL-TIME VIDEO STABILIZATION WITH A NOVEL LEAST SQUARES FORMULATION |
| Authors |
Jianwei Ke, Alex Watras, Jae-Jun Kim, Hewei Liu, Hongrui Jiang, Yu Hen Hu, University of Wisconsin-Madison, United States |
| Session | IVMSP-15: Local Descriptors and Texture |
| Location | Gather.Town |
| Session Time: | Wednesday, 09 June, 15:30 - 16:15 |
| Presentation Time: | Wednesday, 09 June, 15:30 - 16:15 |
| Presentation |
Poster
|
| Topic |
Image, Video, and Multidimensional Signal Processing: [IVARS] Image & Video Analysis, Synthesis, and Retrieval |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
We present a novel video stabilization algorithm (LSstab) that removes unwanted motions in real-time. LSstab is based on a novel least squares formulation of the smoothing cost function to alleviate the undesirable camera jitter. A recursive least square solver is derived to minimize the smoothing cost function with an $O(N)$ computation complexity. LSstab is evaluated using a suite of publicly available videos against the state of the art video stabilization methods. Results show LSstab reaches comparable or better performance, achieving real-time processing speed when a GPU is used. |
