A robust video stabilization method for camera shoot in mobile devices using GMM-based motion estimator

作者全名:"Li, Xinke; Mo, Haofan; Liu, Feng"

作者地址:"[Li, Xinke; Liu, Feng] Chongqing Med Univ, Coll Med Informat, Chongqing 400016, Peoples R China; [Li, Xinke; Mo, Haofan] Chongqing Univ, Sch Microelect & Commun Engn, Chongqing 400044, Peoples R China"

通信作者:"Li, XK (通讯作者),Chongqing Med Univ, Coll Med Informat, Chongqing 400016, Peoples R China.; Li, XK (通讯作者),Chongqing Univ, Sch Microelect & Commun Engn, Chongqing 400044, Peoples R China."

来源:COMPUTERS & ELECTRICAL ENGINEERING

ESI学科分类:COMPUTER SCIENCE

WOS号:WOS:001040352400001

JCR分区:Q1

影响因子:4

年份:2023

卷号:110

期号: 

开始页: 

结束页: 

文献类型:Article

关键词:Video stabilization; Real time; Block-wised feature; Motion estimation; Foreground Segmentation

摘要:"The application of video stabilization methods to mobile devices with low computing power is an important issue. In this study, we aim to provide a robust video stabilization solution for such mobile devices with limited computing resources. We first propose a fast feature extraction method based on a block-wise gradient. Then, we extract motion information through feature point pairs and rebuild the camera path. Finally, the data were smoothed and the corresponding compensation matrix was calculated to obtain a stable video. However, large foreground objects may lead to incorrect motion estimation. Thus, we propose a fast foreground segmentation method based on GMM for jitter scenes to eliminate foreground features and obtain a more accurate camera trajectory. The experimental results show that the proposed method is robust against large foreground objects and exhibits good real-time performance."

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