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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