Hyundai Motor. has filed a patent for a method and apparatus to generate depth maps using volumetric features. The technology involves encoding base images from surround-view cameras, creating single feature maps, and projecting them into a 3D space to generate depth maps. The process includes decoding the volumetric feature using a depth decoder. GlobalData’s report on Hyundai 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 Hyundai Motor, Battery management systems was a key innovation area identified from patents. Hyundai Motor's grant share as of January 2024 was 47%. Grant share is based on the ratio of number of grants to total number of patents.
Generating depth maps for surround-view images using volumetric features
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The patent application (Publication Number: US20240037791A1) describes a method for generating a depth map using a volumetric feature. The process involves obtaining a surround-view image through monocular cameras, generating multi-scale image features, creating a single feature map for the base image, encoding depth information, projecting the result into a three-dimensional space, and decoding the volumetric feature to produce a depth map. The method also includes extracting local three-dimensional features, using a volumetric encoder, and transforming the volumetric feature into a projected image feature based on camera parameters.
Furthermore, the patent application includes details about the apparatus for generating the depth map, which consists of a memory storing programs and a processor executing these programs. The processor is responsible for obtaining the surround-view image, generating multi-scale image features, creating a single feature map, encoding depth information, projecting into three-dimensional space, and decoding to generate the depth map. Additionally, a computer-readable recording medium is provided with a program for executing the method described in the patent application. This innovative method offers a detailed and systematic approach to generating depth maps using monocular cameras and volumetric features, potentially enhancing various applications in the field of computer vision and image processing.
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