Comparison of Motion Smoothing Strategies for Video Stabilization using Parametric Models
Javier Sánchez
published
2017-11-26
reference
Javier Sánchez, Comparison of Motion Smoothing Strategies for Video Stabilization using Parametric Models, Image Processing On Line, 7 (2017), pp. 309–346. https://doi.org/10.5201/ipol.2017.209

Communicated by Laurent Oudre
Demo edited by Javier Sánchez

This IPOL article is related to a companion publication in the SIAM Journal on Imaging Sciences:
J. Sánchez and J-M. Morel, "Motion Smoothing Strategies for Video Stabilization" SIAM Journal on Imaging Sciences, in press, 2017.

Abstract

This paper is devoted to a rigorous implementation and to an exhaustive comparison of video stabilization techniques. These techniques aim at removing the undesirable effects of camera shake. They first estimate a global transform from frame to frame, which can be a translation, a similarity, an affine map or a homography. This generates a signal that can be smoothed and used to compensate the noisy transform signal. This paper compares all classic smoothing methods and their boundary conditions. It also analyzes two algorithms to crop the video after stabilization. The stabilization results are displayed in a scale-space form permitting to extract valuable information about ego-motion such as its frequencies and its general tendencies.

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