NVIDIA had 78 patents in edge computing during Q1 2024. NVIDIA Corp has filed patents for sensor parameter calibration techniques for in-cabin monitoring systems, compressed grid-based graph representations for efficient graph-mapped computing applications, parallel edge decimation on high resolution meshes, machine learning models for robot control, and calibration techniques for interior depth sensors and image sensors in in-cabin monitoring systems. These patents focus on improving the accuracy and efficiency of various monitoring and computing applications. GlobalData’s report on NVIDIA gives a 360-degree view of the company including its patenting strategy. Buy the report here.

NVIDIA grant share with edge computing as a theme is 19% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Sensor calibration using fiducial markers for in-cabin monitoring systems and applications (Patent ID: US20240104941A1)

The patent filed by NVIDIA Corp. describes sensor parameter calibration techniques for in-cabin monitoring systems, specifically focusing on an occupant monitoring system (OMS) used in vehicles or machines. The system involves determining calibration parameters for interior image sensors to reference 2D captured images to an in-cabin 3D coordinate system. The processing unit detects fiducial points in interior space images, determines 2D and 3D coordinates for these points, computes a calibration parameter, and configures operations based on this parameter. The system can be used for various applications, including autonomous machine control, simulation operations, deep learning, and virtual reality content generation.

The claims detail the system's components and functions, such as computing transforms between 2D and 3D coordinates, detecting fiducial points using computer vision algorithms, determining calibration accuracy metrics, and translating image spaces between sensors. The processor, a key element of the system, determines image and 3D coordinates, computes transforms, and stores calibration parameters. It can be used in various applications like autonomous machine control, simulation operations, and virtual reality content generation. The method outlined involves determining occupant information based on sensor images calibrated using fiducial markers, showcasing the system's practical application in monitoring and assessing occupants in vehicles or machines.

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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.