ICASSP 2021accepted0 citations

Efficient Real-Time Video Stabilization with a Novel Least Squares Formulation

Jianwei Ke, Alex J. Watras, Jae-Jun Kim, Hewei Liu, Hongrui Jiang, Yu Hen Hu

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.

BibTeX
@inproceedings{icassp2021_efficientrealtim,
  title = {Efficient Real-Time Video Stabilization with a Novel Least Squares Formulation},
  author = {Jianwei Ke and Alex J. Watras and Jae-Jun Kim and Hewei Liu and Hongrui Jiang and Yu Hen Hu},
  booktitle = {ICASSP 2021},
  year = {2021}
}
Efficient Real-Time Video Stabilization with a Novel Least Squares Formulation · ICASSP 2021