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

被引：2

作者：

Li, Baotong ^{[1
]}

Chen, Yangzhou ^{[1
]}

Ren, Jianqiang ^{[1
]}

Cheng, Lan ^{[1
]}

机构：

[1] Beijing Univ Technol, Coll Metropolitan Transportat, Beijing Key Lab Transportat Engn, Beijing 100 Pingleyuan, Beijing 100124, Peoples R China

来源：

INFORMATION TECHNOLOGY AND INTELLIGENT TRANSPORTATION SYSTEMS, VOL 2 | 2017年 / 455卷

基金：

中国国家自然科学基金;

关键词：

Video stabilization; Motion estimation; Feature matching; Histogram clustering; DIGITAL IMAGE STABILIZATION; TRACKING; SYSTEM;

D O I：

10.1007/978-3-319-38771-0_31

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：315 / 325

页数：11

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