Abstract: Systems arranged to implement methods for positioning a semantic landmark in an image from the real world during a continuous motion of a monocular camera providing said image, using in combination image information from the camera and GPS information, wherein the camera parameters are unknown a priori and are estimated in a self-calibration step, wherein in a subsequent step positioning of the landmarks is completed using one of camera ego motion and depth estimation.

Abstract: An AI based change detection system for executing a method to detect changes in geo-tagged videos to update HD maps, the method employing a neural network of modular components including a keyframe extraction module for processing two or more videos relating to separate traversals of an area of interest to which the HD map which is to be updated relates, a deep neural network module processing output of the keyframe extraction module, a change detection module processing output of the deep neural network module, and an auxiliary computations module which is designed to aid the change detection module.

Abstract: A method and system for generating ground-truth annotations for object detection and classification for roadside objects in video data, wherein the method uses in combination an object detector to detect object instances of roadside objects in each frame of a video, a visual object tracker to detect and track the roadside object across the remaining video frames the roadside object appears in and clusters these detected object instances of the same roadside object into an object track, a trajectory analyzer to filter out object tracks that are unlikely from roadside objects, a classification model to classify each object instance in the object track into a predefined roadside object class, after which the object track as a whole is classified by seeking consensus among the individual object instance classifications in the object track, and classification consistency to determine whether the resulting roadside object class can be assigned automatically to the concerning object track as a ground-truth annotatio

Abstract: Systems arranged to implement methods for positioning a semantic landmark in an image from the real world during a continuous motion of a monocular camera providing said image, using in combination image information from the camera and GPS information, wherein the camera parameters are unknown a priori and are estimated in a self-calibration step, wherein in a subsequent step positioning of the landmarks is completed using one of camera ego motion and depth estimation.