Dynamic Object Detection Using Improved Vibe for RGB-D SLAM
Yue Xu, Qing Guo, Juan Chen
- 发表年份
- 2018
- 引用次数
- 2
摘要
Simultaneous localization and mapping (SLAM) is essential for autonomous navigation of mobile robot. However, dynamic objects, such as walking people, can seriously degrade the performance of SLAM. An improved Vibe (IVibe) algorithm that bases on background frame updating is proposed to detect dynamic objects in RGB-D SLAM. The background frame is updated according to the occupancy rate of foreground points and the changing value of the depth pixels. The homography matrix is used to eliminate the space mismatch between the background frame and the current frame. The foreground point inspection method is applied in pixel classification to deal with the "ghost" point. The experiment results show that the IVibebased approach can detect the dynamic objects in RGB-D SLAM effectively.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002