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

Citation Author(s):
Jianwei Ke, Alex J Watras, Jae-Jun Kim, Hewei Liu, Hongrui Jiang, Yu Hen Hu
Submitted by:
Jianwei Ke
Last updated:
16 June 2021 - 11:31am
Document Type:
Presentation Slides
Document Year:
2021
Event:
Presenters:
Jianwei Ke
Paper Code:
1671
 

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.

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