Visual place recognition for unmanned vehicles in city-scale challenging environments - Peng, Guohao (Nanyang Technological University, 2023)
Large-scale visual place recognition (VPR) involves retrieving reference images that depict the same location of the given query image. It can be applied to loop closure detection within Simultaneous Locations and Mapping (SLAM) for robot systems. With the rapid development of mobile robots, long-term navigation poses greater challenges to the VPR task. For example, the same place may undergo extreme appearance changes due to different illumination, weather, and seasonal conditions. The task difficulty is also increased by partial occlusion and dynamic objects. Additionally, a robot may revisit the same place with different viewpoints. Therefore, large-scale visual place recognition under challenging conditions has raised widespread concerns in both Computer Vision and Robotics communities.