Faro Technologies. has been granted a patent for a method that trains a machine learning model using data from 3D imagers. This method generates disparity maps from pairs of images captured while projecting light patterns onto objects, enhancing 3D imaging capabilities. GlobalData’s report on Faro Technologies 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 Faro Technologies, Lidar-based object detection was a key innovation area identified from patents. Faro Technologies's grant share as of June 2024 was 52%. Grant share is based on the ratio of number of grants to total number of patents.
Machine learning model for generating disparity maps from images
The patent US12047550B2 outlines a method and system for generating disparity maps and point clouds from pairs of images captured by three-dimensional (3D) imagers. The method begins with the collection of training data, which includes pairs of training images where light patterns are projected onto objects. This data is used to create a machine learning model capable of generating disparity maps from captured image pairs. The captured images consist of a left and a right camera image, both taken while projecting a light pattern onto an object. The model can be based on either a disparity neural network or a random forest algorithm, and it is designed to produce disparity maps that may include ground truth and visualized disparity maps.
The system described in the patent includes a first scanner with a left camera, a right camera, and a projector, which captures training images by projecting a light pattern onto an object. A processing system generates a machine learning model from these images and a corresponding disparity map. Additionally, a second scanner operates similarly to capture another set of images and generate a second disparity map using the previously trained model. The methods also encompass generating point clouds from the disparity maps through triangulation techniques, which may include stereo calibration. Overall, the patent presents a comprehensive approach to enhancing 3D imaging capabilities through advanced machine learning techniques.
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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.
