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Persistent tracking of static scene features using geometry

机译:使用几何形状持久跟踪静态场景特征

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Despite many alternatives to feature tracking problem, iterative least squares solution solving the optical flow constraint has been the most popular approach used by many in the field. This paper attempts to leverage the former efforts to enhance feature tracking methods by introducing a view geometric constraint to the tracking problem. In contrast to alternative geometry based methods, the proposed approach provides a closed form solution to optical flow estimation from image appearance and view geometry constraints. We particularly use invariants in the projective coordinates generated from tracked features that results in a new optical flow equation. This treatment provides persistent tracking of features even when they are occluded. At the end of each tracking loop the quality of the tracked features is judged using both appearance similarity and geometric consistency. Our experiments demonstrate robust tracking performance even when the features are occluded or they undergo appearance changes due to projective deformation of the template.
机译:尽管特征跟踪问题有很多替代方法,但是迭代最小二乘求解光流约束已成为该领域中许多人最常用的方法。本文试图通过将视图几何约束引入跟踪问题来利用前者的努力来增强特征跟踪方法。与基于替代几何的方法相比,所提出的方法为根据图像外观和视图几何约束的光流估计提供了一种封闭形式的解决方案。我们特别在从跟踪特征生成的投影坐标中使用不变式,从而产生新的光流方程。即使这些特征被遮挡,此处理也可以提供特征的持久跟踪。在每个跟踪循环的末尾,使用外观相似性和几何一致性来判断跟踪特征的质量。我们的实验证明了强大的跟踪性能,即使特征被遮挡或由于模板的投影变形而发生外观变化时也是如此。

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