Feature Tracking Evaluation for Pose Estimation in Underwater Environments
Feature Tracking Evaluation for Pose Estimation in Underwater Environments
复制标题
水下环境中姿态估计的特征跟踪评估
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
G. Dudek
中科院分区：
文献类型：
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作者：
F. Shkurti;Ioannis M. Rekleitis;G. Dudek
本文介绍了一种用于水下机器人的六自由度位姿估计算法的计算机视觉部分。我们的目标是评估哪些特征跟踪器使我们能够尽可能快地准确估计特征的3D位置。为此，我们在不同的水下数据集上对可用的检测器、描述符和匹配方案进行了评估。我们感兴趣的是在这个搜索空间中从运动算法中识别适合用于结构的组合，以及更一般地，使用单目摄像机的视觉辅助定位算法。我们的评估包括所需属性的逐帧统计，以及以跟踪特征的长度表示的稳健性度量。我们根据每帧提取的关键点的数量、特征轨迹的长度、每帧的平均跟踪时间、帧之间的误判匹配数来比较每种组合的匹配度。使用了几个数据集，在不同的水下位置和不同的光照和能见度条件下收集。
In this paper we present the computer vision component of a 6DOF pose estimation algorithm to be used by an underwater robot. Our goal is to evaluate which feature trackers enable us to accurately estimate the 3D positions of features, as quickly as possible. To this end, we perform an evaluation of available detectors, descriptors, and matching schemes, over different underwater datasets. We are interested in identifying combinations in this search space that are suitable for use in structure from motion algorithms, and more generally, vision-aided localization algorithms that use a monocular camera. Our evaluation includes frame-by-frame statistics of desired attributes, as well as measures of robustness expressed as the length of tracked features. We compare the fit of each combination based on the following attributes: number of extracted key points per frame, length of feature tracks, average tracking time per frame, number of false positive matches between frames. Several datasets were used, collected in different underwater locations and under different lighting and visibility conditions.