ADOBE. has filed a patent for using machine learning models to simulate three-dimensional garment deformation on character bodies in motion, including collision handling. The method involves receiving input parameters, generating garment vertices, detecting penetration, and adjusting vertices to prevent collision. 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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According to GlobalData’s company profile on ADOBE, User behaviour analysis was a key innovation area identified from patents. ADOBE's grant share as of January 2024 was 75%. Grant share is based on the ratio of number of grants to total number of patents.
Machine learning for 3d garment deformation during character motion
A computer-implemented method for generating realistic garment deformations on a character body has been patented. The method involves receiving input parameters defining the character body and garment, generating garment vertices, detecting penetration of garment vertices into the character body, and adjusting the position of the penetrating vertices using neural networks. The process includes determining distance values for each vertex, identifying penetration based on negative distance values, calculating gradients, predicting offset distances, and updating vertex positions to ensure they are outside the character body.
The patented system comprises a memory component and a processing device that executes operations to implement the method described. By utilizing neural networks, the system can accurately detect and rectify garment penetration issues on character bodies in digital environments. The system processes input parameters, generates garment vertices, identifies penetration, calculates gradients, predicts offset distances, and updates vertex positions. This innovative approach ensures that virtual garments fit realistically on character bodies without intersecting or penetrating the surface, enhancing the visual quality and accuracy of digital simulations and animations.
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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.
