Naver has been granted a patent for a visual localization method that integrates feature point maps from different viewpoints—road and aerial. The method compensates for positional differences and utilizes correspondences between images to enhance localization accuracy. GlobalData’s report on Naver 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 Naver, Recommender systems was a key innovation area identified from patents. Naver's grant share as of June 2024 was 58%. Grant share is based on the ratio of number of grants to total number of patents.
Visual localization using integrated feature point maps
The patent US12046003B2 outlines a visual localization method and system that integrates feature point maps generated from two distinct viewpoints: a road viewpoint and an aerial viewpoint. The method involves creating a first feature point map using data from street view images captured at the road level, and a second feature point map derived from rendered images based on 3D model data of the outdoor space. The integration of these maps is achieved by compensating for positional differences between corresponding points in the two maps, which includes calculating feature point correspondences and estimating changes in camera pose. The final visual localization process utilizes this integrated map data to accurately determine the location based on input images.
Additionally, the system comprises processing circuitry within a mobile or autonomous driving device, which executes the aforementioned steps. The method allows for the detection of feature points from cropped street view images and the generation of 3D points based on these features. The second feature point map is created by rendering images from a virtual camera perspective, utilizing 3D model data generated from aerial images. The system also includes error optimization techniques to refine camera pose estimates and can match feature point maps through scan matching. This innovative approach enhances the accuracy and reliability of visual localization in various applications, including navigation and autonomous driving.
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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.
