Simultaneous Video Stabilization and Moving Object Detection in Turbulence

Turbulence mitigation refers to the stabilization of videos with nonuniform deformations due to the influence of optical turbulence. Typical approaches for turbulence mitigation follow averaging or dewarping techniques. Although these methods can reduce the turbulence, they distort the independently...

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Bibliographic Details
Published in:	IEEE transactions on pattern analysis and machine intelligence Vol. 35; no. 2; pp. 450 - 462
Main Authors:	Oreifej, O., Xin Li, Shah, M.
Format:	Journal Article
Language:	English
Published:	Los Alamitos, CA IEEE 01.02.2013 IEEE Computer Society The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Applied sciences Artificial Intelligence Atmospheric optics Atmospheric turbulences effects Computational fluid dynamics Computer science; control theory; systems Data Interpretation, Statistical Distortion Equations Exact sciences and technology Fluid flow Force Fundamental areas of phenomenology (including applications) Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Mathematical model Matrix decomposition Minimization Motion moving object detection Norms Object detection Optics Optimization particle advection Pattern Recognition, Automated - methods Pattern recognition. Digital image processing. Computational geometry Photography - methods Physics rank optimization Reproducibility of Results restoring force Sensitivity and Specificity Stabilization Studies Three-term decomposition Turbulence turbulence mitigation Turbulence models Turbulent flow Video Recording - methods Averaging method Stabilization Video signal Modeling Optimization turbulence mitigation Gaussian noise restoring force Robustness Three-term decomposition particle advection rank optimization Computer vision Motion estimation Video technique Minimization Translation motion Dimension reduction Gaussian process Atmospheric turbulence Non uniform field Object detection moving object detection Adaptive optics Moving body
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
Online Access:	Get full text
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Summary:	Turbulence mitigation refers to the stabilization of videos with nonuniform deformations due to the influence of optical turbulence. Typical approaches for turbulence mitigation follow averaging or dewarping techniques. Although these methods can reduce the turbulence, they distort the independently moving objects, which can often be of great interest. In this paper, we address the novel problem of simultaneous turbulence mitigation and moving object detection. We propose a novel three-term low-rank matrix decomposition approach in which we decompose the turbulence sequence into three components: the background, the turbulence, and the object. We simplify this extremely difficult problem into a minimization of nuclear norm, Frobenius norm, and 21 norm. Our method is based on two observations: First, the turbulence causes dense and Gaussian noise and therefore can be captured by Frobenius norm, while the moving objects are sparse and thus can be captured by 21 norm. Second, since the object's motion is linear and intrinsically different from the Gaussian-like turbulence, a Gaussian-based turbulence model can be employed to enforce an additional constraint on the search space of the minimization. We demonstrate the robustness of our approach on challenging sequences which are significantly distorted with atmospheric turbulence and include extremely tiny moving objects.
Bibliography:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 content type line 23 ObjectType-Article-1 ObjectType-Feature-2
ISSN:	0162-8828 1939-3539 2160-9292 1939-3539
DOI:	10.1109/TPAMI.2012.97