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2017 | OriginalPaper | Buchkapitel

A Fast Video Stabilization Method Based on Feature Matching and Histogram Clustering

verfasst von : Baotong Li, Yangzhou Chen, Jianqiang Ren, Lan Cheng

Erschienen in: Information Technology and Intelligent Transportation Systems

Verlag: Springer International Publishing

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Abstract

Stable video has a significant effect on video based traffic parameters extraction system. This paper proposed a fast video stabilization method based on feature matching and histogram clustering. Firstly, the method extract ORB feature points on sub-images which are set in adjacent frames and then matches them based on Hamming Distance. Secondly, the motion consistency principle combined with histogram clustering is used to get correct matches which can be used to calculate the parameters of the affine transformation matrix. Finally, after filtering those parameters, stable frame can be obtained by warping the original frame using the affine transformation matrix. Experimental results show that the proposed method can effectively stabilize videos with low complexity in real time.

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Metadaten
Titel
A Fast Video Stabilization Method Based on Feature Matching and Histogram Clustering
verfasst von
Baotong Li
Yangzhou Chen
Jianqiang Ren
Lan Cheng
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-38771-0_31