The stability and quantity of feature matching in video sequence is one of the key issues for feature tracking and some relevant applications. The existing matching methods are based on feature detection, which is usually affected by illumination conditions, noise or occlusions, and this will directly influence matching results. In this paper, we propose an accurate prediction method for interest point estimation in video sequence by extracting the stable mapping for each undetected point in its suitable projective plane, which is based on coplanar feature points that have already been detected in adjacent frames. The proposed prediction method breaks the limitation of the previous approaches that largely rely on feature detection. Our experiments show that our method not only predicts features accurately, but also enriches the correspondences, which prolongs the track length of features.

中文翻译：

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视频序列中基于个体投影平面的特征点精确估计

视频序列中特征匹配的稳定性和数量是特征跟踪和一些相关应用的关键问题之一。现有的匹配方法基于特征检测，通常受光照条件、噪声或遮挡的影响，这将直接影响匹配结果。在本文中，我们提出了一种准确的视频序列兴趣点估计预测方法，通过提取每个未检测点在其合适的投影平面中的稳定映射，这是基于在相邻帧中已经检测到的共面特征点。所提出的预测方法打破了先前主要依赖特征检测的方法的局限性。我们的实验表明，我们的方法不仅准确预测了特征，而且丰富了对应关系，