Santiago Cortés, Arno Solin, Esa Rahtu, Juho Kannala
TL;DR通过提供高质量的真实世界数据和多种原始传感器数据,具有六自由度地面真值的计算机视觉基准集,比较 Google Tango、ARCore 和 Apple ARKit 的视觉惯性跟踪与两种学术方法。
Abstract
The lack of realistic and open benchmarking datasets for pedestrian
visual-inertial odometry has made it hard to pinpoint differences in published
methods. Existing datasets either lack a full six degree-of-freed