Motion estimation based feature selection for visual SLAM

作     者：孟旭炯 Jiang Rongxin Zhou Fan Chen Yaowu 

作者机构：Institute of Advanced Digital Technologies ＆ Instrumentation Zhejiang University Hangzlaou 310027 P.R.China 

出 版 物：《High Technology Letters》 (高技术通讯（英文版）)

年 卷 期：2011年第17卷第4期

页      面：433-438页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 081001[工学-通信与信息系统] 0803[工学-光学工程] 

基　　金：the National High Technology Research and Development Programme of China(2003AA1Z2130) 

主　　题：visual SLAM feature selection motion estimation computational efficiency consistency extended Kalman filter (EKF) 

摘      要：Feature selection is always an important issue in the visual SLAM （simultaneous location and mapping） literature. Considering that the location estimation can be improved by tracking features with larger value of visible time, a new feature selection method based on motion estimation is proposed. First, a k-step iteration algorithm is presented for visible time estimation using an affme motion model; then a delayed feature detection method is introduced for efficiently detecting features with the maximum visible time. As a means of validation for the proposed method, both simulation and real data experiments are carded out. Results show that the proposed method can improve both the estimation performance and the computational performance compared with the existing random feature selection method.