Search Results for "visual\"

RTAB-Map (Real-Time Appearance-Based Mapping) is a RGB-D, Stereo and Lidar Graph-Based SLAM approach based on an incremental appearance-based loop closure detector. The loop closure detector uses a bag-of-words approach to determine how likely a new image comes from a previous location or a new location. When a loop closure hypothesis is accepted, a new constraint is added to the map’s graph, then a graph optimizer minimizes the errors in the map. A memory management approach is used to...

3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV queries. ...

The intention behind this Lidar Visualisation Toolbox is to provide an easy-to-use, stand-alone application to create visualisations from high-resolution airborne LIDAR-based digital elevation data. LiVT also includes tools like raster file creation from xyz point clouds. A few mouse clicks and some processing time should be enough to go from an xyz ASCII file to a grey-scale SVF image, an LRM map or a percentage map of cumulative visibility. As LiVT does not include a data viewer,...