Distance estimation with 2.5D anchors and its application to robot navigation

ROBOMECH Journal

Yuki Saito¹  Masaya Nomura²  Hirotaka Hachiya²  Kazuma Iteya²  Takayuki Nakamura² 

[1] Department of Statistical Science, Graduate University for Advanced Studies, Tachikawa, Japan;Faculty of System Engineering, Wakayama University, Wakayama-shi, Japan

关键词: Deep learning;    Monocular camera image;    Distance estimation;    Navigation;   

DOI  :  10.1186/s40648-018-0119-5

学科分类：人工智能

来源: Springer

【 摘 要 】

Estimating the distance of a target object from a single image is a challenging task since a large variation in the object appearance makes the regression of the distance difficult. In this paper, to tackle such the challenge, we propose 2.5D anchors which provide the candidate of distances based on a perspective camera model. This candidate is expected to relax the difficulty of the regression model since only the residual from the candidate distance needs to be taken into account. We show the effectiveness of the regression with our proposed anchors, by comparing with ordinary regression methods and state-of-the-art 3D object detection methods, through Pascal 3D+ TV monitor and KITTI car experiments. In addition, we also show an example of practical uses of our proposed method in a real-time system, robot navigation, by integrating with ROS-based simultaneous localization and mapping.

【 授权许可】

CC BY