计算机视觉
人工智能
图像稳定
图像扭曲
单应性
计算机科学
特征(语言学)
旋转(数学)
摄像机自动校准
帧(网络)
跟踪(教育)
摄像机切除
图像(数学)
数学
电信
语言学
统计
哲学
投射试验
射影空间
心理学
教育学
作者
Shuaicheng Liu,Yinting Wang,Lu Yuan,Jiajun Bu,Ping Tan,Jian Sun
标识
DOI:10.1109/cvpr.2012.6247662
摘要
Previous video stabilization methods often employ homographies to model transitions between consecutive frames, or require robust long feature tracks. However, the homography model is invalid for scenes with significant depth variations, and feature point tracking is fragile in videos with textureless objects, severe occlusion or camera rotation. To address these challenging cases, we propose to solve video stabilization with an additional depth sensor such as the Kinect camera. Though the depth image is noisy, incomplete and low resolution, it facilitates both camera motion estimation and frame warping, which make the video stabilization a much well posed problem. The experiments demonstrate the effectiveness of our algorithm.
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