Motion estimation based feature selection for visual SLAM  

作　　者：孟旭炯 Jiang Rongxin Zhou Fan Chen Yaowu 

机构地区：[1]Institute of Advanced Digital Technologies ＆ Instrumentation, Zhejiang University, Hangzlaou 310027, P.R.China

出　　处：《High Technology Letters》2011年第4期433-438,共6页高技术通讯（英文版）

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.

关 键 词：visual SLAM feature selection motion estimation computational efficiency CONSISTENCY extended Kalman filter （EKF） 

分 类 号：TN919.81[电子电信—通信与信息系统] TH742.64[电子电信—信息与通信工程]