Hinge Health has been granted a patent for systems and methods to estimate 3D joint locations from 2D images using convolutional neural networks. The technology involves determining 2D joint locations, expanding depth resolution, and combining data to generate 3D joint positions. GlobalData’s report on Hinge Health 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 Hinge Health, AI-assisted medical imaging was a key innovation area identified from patents. Hinge Health's grant share as of February 2024 was 17%. Grant share is based on the ratio of number of grants to total number of patents.
Estimating 3d joint location of skeleton joints from images
A recently granted patent (Publication Number: US11875529B2) discloses a method and system for estimating three-dimensional (3D) positions of joints in an image containing a person. The invention involves obtaining a two-dimensional (2D) image, determining a 2D joint skeleton and heatmap, applying them to a convolutional neural network with 3D convolutional layers to estimate depth for each joint, and constructing a 3D joint skeleton. Additional operations include identifying the person in the image, applying segments to 2D convolutional layers, and utilizing max pooling layers to reduce resolution before combining 2D locations with estimated depths.
Furthermore, the patent describes a method for estimating 3D joint positions by analyzing an image segment. This method involves obtaining a 2D joint heatmap, applying it to a convolutional neural network with 3D convolutional layers to expand depth resolution, and combining 2D locations with estimated depths for each joint. The process includes creating the 2D joint heatmap based on a 2D joint skeleton, utilizing max pooling layers, and applying both 2D and 3D convolutional layers. The patent also covers a computing system implementing these methods to estimate 3D joint positions of a human or object in an image, showcasing the practical application of the technology in real-world scenarios.
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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.
