Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland.
Sensors (Basel). 2021 Nov 19;21(22):7687. doi: 10.3390/s21227687.
The goal of the WrightBroS project is to design a system supporting the training of pilots in a flight simulator. The desired software should work on smart glasses supplementing the visual information with augmented reality data, displaying, for instance, additional training information or descriptions of visible devices in real time. Therefore, the rapid recognition of observed objects and their exact positioning is crucial for successful deployment. The keypoint descriptor approach is a natural framework that is used for this purpose. For this to be applied, the thorough examination of specific keypoint location methods and types of keypoint descriptors is required first, as these are essential factors that affect the overall accuracy of the approach. In the presented research, we prepared a dedicated database presenting 27 various devices of flight simulator. Then, we used it to compare existing state-of-the-art techniques and verify their applicability. We investigated the time necessary for the computation of a keypoint position, the time needed for the preparation of a descriptor, and the classification accuracy of the considered approaches. In total, we compared the outcomes of 12 keypoint location methods and 10 keypoint descriptors. The best scores recorded for our database were almost 96% for a combination of the ORB method for keypoint localization followed by the BRISK approach as a descriptor.
WrightBroS 项目的目标是设计一个支持在飞行模拟器中培训飞行员的系统。理想的软件应在智能眼镜上运行，利用增强现实数据补充视觉信息，实时显示例如额外的培训信息或可见设备的描述。因此，成功部署的关键是快速识别观察到的物体及其准确位置。关键点描述符方法是用于此目的的自然框架。为此，首先需要彻底检查特定的关键点定位方法和关键点描述符的类型，因为这些是影响方法整体准确性的关键因素。在本研究中，我们准备了一个专门的数据库，其中包含 27 种飞行模拟器的各种设备。然后，我们使用它来比较现有的最先进技术并验证其适用性。我们研究了计算关键点位置所需的时间、准备描述符所需的时间以及所考虑方法的分类准确性。总共，我们比较了 12 种关键点定位方法和 10 种关键点描述符的结果。对于我们的数据库，记录的最佳分数几乎接近 96%，是 ORB 方法定位关键点，然后 BRISK 方法作为描述符的组合。
