| CPC G01C 21/3867 (2020.08) [G01C 21/3859 (2020.08); G06F 16/29 (2019.01); G06V 10/764 (2022.01)] | 18 Claims |
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1. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least:
receive a rasterized image representative of map geometry within a geographic area, wherein each pixel of the rasterized image reflecting probe data is encoded with at least one property representing at least one component of probe data associated with the map geometry, wherein the at least one component comprises one or more of a travel speed, an average heading angle, a lane marking observation, or a probe data point count;
apply an object detection model to the rasterized image to automatically detect objects in the rasterized image, wherein the object detection model is a machine learning model trained using training data to identify map data objects and geometries;
generate a list of bounding boxes together with classes of objects within the bounding boxes based on the object detection model, wherein the list of bounding boxes is a list defining each bounding box as a coordinate pair of a center of the bounding box, a width of the bounding box, a height of the bounding box, and an orientation of the bounding box;
generate map data from the list of bounding boxes and the classes of objects within the bounding boxes by reconstructing, from each bounding box represented as the coordinate pair of the center of the bounding box, the width of the bounding box, the height of the bounding box, and the orientation of the bounding box, endpoints of each line segment in map data; and
update a map in a map database with the map data.
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