人工智能
计算机科学
稳健性(进化)
计算机视觉
背景减法
合成
像素
匹配(统计)
图像配准
高动态范围
图像(数学)
模式识别(心理学)
计算机图形学(图像)
数学
动态范围
生物化学
化学
统计
基因
作者
Peter Sand,Seth Teller
标识
DOI:10.1145/1015706.1015765
摘要
This paper describes a method for bringing two videos (recorded at different times) into spatiotemporal alignment, then comparing and combining corresponding pixels for applications such as background subtraction, compositing, and increasing dynamic range. We align a pair of videos by searching for frames that best match according to a robust image registration process. This process uses locally weighted regression to interpolate and extrapolate high-likelihood image correspondences, allowing new correspondences to be discovered and refined. Image regions that cannot be matched are detected and ignored, providing robustness to changes in scene content and lighting, which allows a variety of new applications.
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