Proceedings of the 2019 International Conference on Modeling, Simulation, Optimization and Numerical Techniques (SMONT 2019)

A Novel Joint Optimization Method for Adaptive Hand-held Video Stabilization Based on Spatial-temporal Consistency

Authors
Xiao Li, Shuai Li, Hong Qin, Aimin Hao
Corresponding Author
Shuai Li
Available Online April 2019.
DOI
10.2991/smont-19.2019.26How to use a DOI?
Keywords
hand-held Camera; adaptive video stabilization; spatial structure consistency; feature-centric EMD; self-adaptive IMF selection; video extrapolation and interpolation
Abstract

Video stabilization for hand-held camera is vital in many high-level video enhancement applications. Although quite a few proposed approaches have achieved remarkable success in recent years, many technical challenges still prevail for video (from hand-held camera) containing wide-range scenes and highly-variable objects. In particular, we are lacking effective and versatile strategies to adaptively handle saliency preservation, parallax diminution, self-adaptive smoothing, cropping area decrement and video completeness in a consistent spatial-temporal fashion. To ameliorate, this paper develops a novel, joint optimization method to successively respect spatial structure consistency and temporal feature constraints. Our aim is to devise a new adaptive video stabilization technique by resorting to new modeling strategies. This paper’s key originality is hinged upon joint utility of both self-adaptive intrinsic mode functions (IMFs) based on empirical mode decomposition (EMD) in temporal domain for video signal and mesh-structure constraint enforcement in the spatial domain. As a result, our new approach can optimize camera trajectory of wobbly video, and synchronously fine-tune the camera path based on key features to make the shaking video much closer to the original trend. To validate our joint optimization approach for adaptive video stabilization, we conduct comprehensive experiments on public benchmarks, and make extensive and quantitative evaluations with available state-of-the-art methods as well as popular commercial software. All of our experiments demonstrate the advantages of the joint optimization method in terms of versatility, accuracy, and efficiency.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2019 International Conference on Modeling, Simulation, Optimization and Numerical Techniques (SMONT 2019)
Series
Advances in Intelligent Systems Research
Publication Date
April 2019
ISBN
10.2991/smont-19.2019.26
ISSN
1951-6851
DOI
10.2991/smont-19.2019.26How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xiao Li
AU  - Shuai Li
AU  - Hong Qin
AU  - Aimin Hao
PY  - 2019/04
DA  - 2019/04
TI  - A Novel Joint Optimization Method for Adaptive Hand-held Video Stabilization Based on Spatial-temporal Consistency
BT  - Proceedings of the 2019 International Conference on Modeling, Simulation, Optimization and Numerical Techniques (SMONT 2019)
PB  - Atlantis Press
SP  - 108
EP  - 120
SN  - 1951-6851
UR  - https://doi.org/10.2991/smont-19.2019.26
DO  - 10.2991/smont-19.2019.26
ID  - Li2019/04
ER  -