Woven Planet North America, Inc.

Lyft, Inc.

Wilhelm Richert

Clemens Marschner

Thomas Schiwietz

Darko Zikic

Holger H Rapp

Nikolai Morin

Patrick Dubroy

The present invention relates to a method of generating an overhead view image of an area. More particularly, the present invention relates to a method of generating a contextual multi-image based overhead view image of an area using ground map data and field of view image data. Various embodiments of the present technology can include methods, systems and non-transitory computer readable media and computer programs configured to receive a plurality of images of the geographical area, determine a ground map of the geographical area, divide the ground map into a plurality of sampling points of the geographical area; and determine a color for each of the plurality of sampling points, wherein the color of each of the sampling points is determined by determining a correlation between the sampling points of the geographical area and color of the sampling points captured in at least one of the plurality of images.

Overhead view image generation

Examples disclosed herein may involve (i) obtaining a first layer of map data associated with sensor data capturing a geographical area, the first layer of map data comprising an aggregated overhead-view image of the geographical area, where the aggregated overhead-view image is generated from aggregated pixel values from a plurality of images associated with the geographical area, (ii) obtaining a second layer of map data, the second layer of map data comprising label data for the geographical area derived from the aggregated overhead-view image of the geographical area, and (iii) causing the first layer of map data and the second layer of map data to be presented to a user for curation of the label data.

Manual curation tool for map data using aggregated overhead views

Examples disclosed herein may involve (i) obtaining 2D image data and 3D sensor data that is representative of an area, (ii) identifying a first set of pixels associated with ephemeral objects detected in the area and a second set of pixels associated with non-ephemeral objects detected in the area, (iii) identifying a first set of ephemeral 3D data points associated with the detected ephemeral objects and a second set of non-ephemeral 3D data points associated with the detected non-ephemeral objects, (iv) mapping the first and second sets of 3D data points to a grid of voxels associated with the area, (v) making a determination that one or more voxels in the grid each contain a threshold extent of ephemeral data points, and (vi) based at least in part on the determination, filtering the 3D sensor data to remove the 3D data points contained within the one or more voxels.

Systems and methods for filtering sensor data to remove data points associated with ephemeral objects

The present invention relates to a method of generating an overhead view image of an area. More particularly, the present invention relates to a method of generating a contextual multi-image based overhead view image of an area using ground map data and field of view image data. Various embodiments of the present technology can include methods, systems and non-transitory computer readable media and computer programs configured to determine a ground map of the geographical area; receiving a plurality of images of the geographical area; process the plurality of images to select a subset of images to generate the overhead view of the geographical area; divide the ground map into a plurality of sampling points of the geographical area; and determine a color of a plurality of patches of the overhead view image from the subset of images, each patch representing each sampling point of the geographical area.

Generating training data from overhead view images

Examples disclosed herein may involve (i) obtaining an aggregated overhead view image of a geographical area that has been generated by a pipeline for generating aggregated overhead view images, the geographical area comprising a plurality of regions, where the aggregated overhead view image is generated from aggregating pixel values from a plurality of source images of the geographical area, (ii) generating one or more reprojection images of one or more of the regions of the geographic area from the aggregated overhead view image, (iii) identifying, from the plurality of source images, one or more source images that capture the one or more regions of the geographical area, (iv) calculating one or more differences between the identified one or more source images and the one or more reprojection images, and (v) determining one or more error corrections to be applied to the pipeline for generating overhead view images.

Mapping pipeline optimization using aggregated overhead view reconstruction

Various embodiments of the present technology can include methods, systems and non-transitory computer readable media and computer programs configured to determine one or more images of a generated overhead view of a geographical area. The generated overhead view is generated from aggregated pixel values determined from correlated pixel values in images of the geographical area. The disclosed approaches identify semantic map features as being present in the images of the overhead perspective of the geographic area. The disclosed approaches extract the semantic map features of the geographical area from the images of the substantially overhead perspective of the geographical area. The disclosed approaches translate the extracted semantic map features to a semantic map layer of a geometric map associated with the geographical area.

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Feldkirchen, Germany

Wilhelm Richert