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使用云阴影推断场景结构和相机校准

Using Cloud Shadows to Infer Scene Structure and Camera Calibration
课程网址: http://videolectures.net/cvpr2010_jacobs_ucsi/  
主讲教师: Nathan Jacobs
开课单位: 华盛顿大学
开课时间: 2010-07-19
课程语种: 英语
中文简介:
我们探索使用云作为结构光照的一种形式来捕捉从静态相机观察到的室外场景的3D结构。我们得出两个线索,将3D距离与由于阴影引起的像素强度变化相关联。第一个提示主要是空间的,与低帧率时间失效一起工作,并且支持估计焦点长度场景结构,直到比例模糊。 secondcue依赖于云运动,并且具有更复杂,但仍然线性的模糊性。我们描述了一种使用空间线索估计深度图的方法和一种结合两种线索的方法。几个户外活动的时间流逝结果表明,这些提示能够估计场景几何形状和相机焦距。
课程简介: We explore the use of clouds as a form of structured lighting to capture the 3D structure of outdoor scenes observed over time from a static camera. We derive two cues that relate 3D distances to changes in pixel intensity due to clouds shadows. The first cue is primarily spatial, works with low frame-rate time lapses, and supports estimating focal length and scene structure, up to a scale ambiguity. The second cue depends on cloud motion and has a more complex, but still linear, ambiguity. We describe a method that uses the spatial cue to estimate a depth map and a method that combines both cues. Results on time lapses of several outdoor scenes show that these cues enable estimating scene geometry and camera focal length.
关 键 词: 静态相机; 空间; 相机焦距
课程来源: 视频讲座网
最后编审: 2020-06-11:chenxin
阅读次数: 33