Walking Human Detection Using Stereo Camera Based on Feature Classification Algorithm of Second Re-projection Error

Shuhuan Wen; Sen Wang; ZhiShang Zhang; Xuebo Zhang; Dan Zhang

doi:10.3389/fnbot.2019.00105

Walking Human Detection Using Stereo Camera Based on Feature Classification Algorithm of Second Re-projection Error

Front Neurorobot. 2019 Dec 18:13:105. doi: 10.3389/fnbot.2019.00105. eCollection 2019.

Authors

Shuhuan Wen¹, Sen Wang¹, ZhiShang Zhang¹, Xuebo Zhang², Dan Zhang³

Affiliations

¹ Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, China.
² Institute of Robotics and Automatic Information System, Nankai University, Tianjin, China.
³ Department of Mechanical Engineering, York University, Toronto, ON, Canada.

Abstract

This paper presents a feature classification method based on vision sensor in dynamic environment. Aiming at the detected targets, a double-projection error based on orb and surf is proposed, which combines texture constraints and region constraints to achieve accurate feature classification in four different environments. For dynamic targets with different velocities, the proposed classification framework can effectively reduce the impact of large-area moving targets. The algorithm can classify static and dynamic feature objects and optimize the conversion relationship between frames only through visual sensors. The experimental results show that the proposed algorithm is superior to other algorithms in both static and dynamic environments.

Keywords: SLAM; classification; dynamic environments; feature target; re-projection error.