Honda Motor has been granted a patent for a system and method for bird’s eye view (BEV) segmentation. The technology involves processing input images from an image sensor to extract features, estimate depth, create a 3D point map, and generate a voxel grid for BEV segmentation. GlobalData’s report on Honda Motor gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Honda Motor, Hydrogen fuel cells was a key innovation area identified from patents. Honda Motor's grant share as of July 2024 was 62%. Grant share is based on the ratio of number of grants to total number of patents.
Bird's eye view segmentation system and method
The granted patent US12073563B2 outlines a system and method for bird's eye view (BEV) segmentation, which involves processing images captured by an image sensor, such as a monocular camera. The system begins by receiving a perspective space image, which is defined by the agent's position and viewing direction. It employs a first neural network to extract features from the input image and estimates a depth map that provides depth values for the image's pixels. This depth map is then used to generate a three-dimensional (3D) point map, which is voxelized into a voxel grid. The voxel grid serves as an indexed image, allowing for feature fusion to predict a feature map. The final output is a BEV segmentation derived from this feature map.
Additionally, the patent specifies that the depth map can be estimated using a second neural network, and the 3D point map may be represented as a point cloud. The BEV segmentation is produced as a BEV image containing segmentation predictions. The method also includes processing the feature map with a BEV neural network, which is trained on a dataset of annotated training images in both perspective and BEV views. This training dataset includes classes associated with various characteristics, enhancing the segmentation process. The patent emphasizes the integration of advanced neural network techniques to improve the accuracy and efficiency of BEV segmentation in real-world applications.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
