ADOBE had eight patents in metaverse during Q2 2024. ADOBE Inc’s patents in Q2 2024 focus on a hybrid approach for camera pose estimation using deep learning-based image matching and match refinement, as well as generating layout-aware background images using a machine learning model trained on mask images. GlobalData’s report on ADOBE gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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ADOBE had no grants in metaverse as a theme in Q2 2024.
Recent Patents
Application: Feature detection for image-based augmented reality (Patent ID: US20240202940A1)
The patent filed by ADOBE Inc. describes a hybrid approach for camera pose estimation using a deep learning-based image matcher and match refinement procedure. The method involves accessing template and content images, estimating feature matches, filtering based on stability, computing camera pose, and rendering video frames with digital elements. The system includes a memory component and processing device to perform these operations for each frame of video in a stream, ensuring accurate camera pose estimation and rendering of digital elements. The method also involves using matching information from prior frames, producing a mask for screen segmentation, and padding the mask to compensate for movement between frames.
Additionally, the patent outlines the process of training a convolutional neural network based on a dataset of target images with random homography, deploying the trained network to an end-user computing device, and utilizing it for accurate camera pose estimation and rendering of digital elements. The non-transitory computer-readable medium stores executable instructions for accessing images, producing high-stability matches, computing camera pose, and rendering video frames with digital elements. The operations also involve using matching information from prior frames, producing a mask for screen segmentation, and deploying the trained network to an end-user computing device for efficient camera pose estimation and rendering.
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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.
