稳健的SSD跟踪增量三维结构估计

Adam Rachmielowski, Dana Cobzas, Martin Jägersand
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引用次数: 7

摘要

虽然从未经校准的图像中进行结构和运动估计的几何方面得到了很好的理解,并且在应用中有很大的前景,但它还没有得到广泛的应用。本文将固态硬盘跟踪与增量结构计算相结合,形成了一个从视频中在线计算运动和结构的系统。我们展示了如何将结构估计和跟踪相结合,从而获得更好的结构和更鲁棒的跟踪。特别是,通过3D结构,我们的方法可以管理可见性约束,添加新的图像补丁来跟踪,因为它们进入视图,并删除被遮挡或失败的图像补丁。这允许跟踪比传统SSD跟踪更大的姿态变化(例如,在新部件进入视图的对象或场景周围)。实验证明了在不相互可见的情况下,从覆盖不同侧面的摄像机轨迹跟踪和捕获场景。
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Robust SSD tracking with incremental 3D structure estimation
While the geometric aspects of structure and motion estimation from uncalibrated images are well understood, and it has great promise in applications, it has not seen widespread use. In this paper we combine SSD tracking with incremental structure computation into a system computing both motion and structure on-line from video. We show how in combination the structure estimation and tracking benefit each other, resulting in both better structure and more robust tracking. Particularly, through the 3D structure, our method can manage visibility constraints, add new image patches to track as they come into view and remove ones that are occluded or fail. This allows tracking over larger pose variations than possible with conventional SSD tracking (e.g. going around an object or scene where new parts come into view.) Experiments demonstrate tracking and capture of a scene from a camera trajectory covering different sides without mutual visibility.
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