图像稳定
计算机科学
运动补偿
补偿(心理学)
计算机视觉
人工智能
移动设备
数字视频
光学(聚焦)
运动估计
视频质量
陀螺仪
人气
运动(物理)
视频处理
质量(理念)
多媒体
工程类
电信
公制(单位)
图像(数学)
哲学
传输(电信)
精神分析
心理学
运营管理
航空航天工程
物理
光学
操作系统
认识论
社会心理学
标识
DOI:10.1109/wcmeim56910.2022.10021453
摘要
In recent years mobile phones and hand-held video cameras are gaining increasing popularity. They allow people to easily film videos but also bring unwanted camera shakes and jitters that affect the video quality. Although mechanical devices, optical devices, and electronic devices can help remove unwanted shakes, those methods are usually expensive and impractical for mobile phones and hand-held cameras. Whereas digital video stabilization techniques only require raw footage maybe plus the gyro data. In this paper, we focus on and compare the effects of different approaches to motion estimation and motion compensation, the two crucial parts of video stabilization algorithms that have a large impact on the quality of video stabilization. Based on that, we conclude that the future of video stabilization lies within using a gyroscope to get accurate camera motion and using neural networks to achieve amazing video quality.
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