The Research Status of Visual Place Recognition

Abstract

Visual place recognition is a challenging problem in the field of Machine Vision and Robotics. Unlike image classification and retrieval, Machine Vision lags far behind humans in place recongniton. Generating image descriptors is the basic problem of VPR. They suppose to be insensitive to changes in illumination and angle of view, and can ensure the stability in the long running process. This paper summarizes the solutions of visual place recognition from two directions: traditional methods and deep learning methods. And explains the key technologies and analyzes the advantages and disadvantages of different methods also the implementation difficulties. In particular, the latest research results are introduced:Using image descriptors generated by semantic segmentation algorithms to solve VPR problems can obtain better performence. Finally, the possibility of using semantic segmentation image descriptors combined with landmark topological relations to solve VPR problems is prospected.