Multi-purpose SLAM Framework for Dynamic Environment

Nowadays, SLAM in the dynamic environment has become a popular topic. This problem is called dynamic SLAM where many solutions have been proposed to segment out the dynamic objects that bring errors to camera tracking and subsequent 3D reconstruction. However, state-of-the-art dynamic SLAM methods face the problems of accuracy and speed, which is due to the fact that one segmentation algorithm cannot guarantee both points at the same time. In this paper, we propose a multi-purpose dynamic SLAM framework to provide a variety of selections for segmentation, each has its applicable scene. The experimental results show that the framework is compatible with different segmentation methods, which improves corresponding existing methods in some aspects.