Object Depth Measurement from Monocular Images Based on Feature Segments
Chuanqi Zhang, Yunfeng Cao, Meng Ding · 2019
Depth measurement technology plays an important role in the field of machine vision, and the depth measurement methods based on monocular vision have received more and more attention. However, previous depth measurement schemes based on single feature points and least squares calculation are susceptible to feature matching errors. To this end, this paper proposes a new object depth measurement method from monocular images based on feature segments. We use two images taken by the same camera and the pose information provided by GPS/IMU device to perform object depth measurement. The experiment based on the visual simulation software shows that the proposed method can improve the accuracy of the measurement results with a good robustness.