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公开(公告)号:US20250078407A1
公开(公告)日:2025-03-06
申请号:US18825252
申请日:2024-09-05
Applicant: DASSAULT SYSTEMES
Inventor: Nicolas BELTRAND , Fivos DOGANIS , Mourad BOUFARGUINE
Abstract: A computer-implemented method for designing a 3D model, which includes providing an initial 3D model in a 3D scene including at least one extruded section, being defined by a set of parameters, receiving a user sketch on the plane perpendicular to the sight of view direction, at each iteration: modifying at least one of said parameters, thereby obtaining a modified 3D model, performing a perspective projection, on a plane perpendicular to the sight of view direction, of the modified 3D mode, thereby obtaining a 2D visible wireframe including the visible inner and outer edges of the modified 3D model, computing an energy including a first term which penalizes an inconsistency between the modified and the initial 3D model, and a second term which penalizes a mismatch between the 2D visible wireframe and the user sketch, said parameters being modified to minimize said energy, and outputting the modified 3D model.
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公开(公告)号:US20230410452A1
公开(公告)日:2023-12-21
申请号:US18336455
申请日:2023-06-16
Applicant: DASSAULT SYSTEMES
Inventor: Nicolas BELTRAND , Fivos DOGANIS
CPC classification number: G06T19/20 , G06T15/20 , G06F30/27 , G06T2219/2016 , G06T2210/12 , G06T2200/24
Abstract: A computer-implemented method for designing at least one 3D model in a 3D scene including receiving a user's 2D sketch and displaying it on a plane, said 2D sketch representing a view of the 3D model to be designed, inferring a 3D primitive based on said 2D sketch, said 3D primitive being oriented and positioned in the 3D scene to match said view, performing a 2D projection of the 3D primitive on said plane, and fitting said 2D projection onto said 2D sketch.
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公开(公告)号:US20250078435A1
公开(公告)日:2025-03-06
申请号:US18825134
申请日:2024-09-05
Applicant: DASSAULT SYSTEMES
Inventor: Nicolas BELTRAND , Fivos DOGANIS , Mourad BOUFARGUINE
Abstract: A computer-implemented method for designing a 3D model in an AR/VR environment including obtaining a 3D model in a 3D scene, the 3D model including at least one extruded section which results from the extrusion of a planar section, said extruded section being defined by a set of parameters, receiving a 3D user sketch in the 3D scene, at each iteration of a plurality of iterations: modifying at least one of said parameters, thereby obtaining a modified 3D model, performing a discretization of the modified 3D model, thereby obtaining a 3D point cloud, computing an energy which comprises a first term which penalizes an inconsistency between the modified 3D model and the initial 3D model, and a second term which penalizes a mismatch between the 3D point cloud and the 3D user sketch, said parameters being modified so as to minimize said energy, and outputting the modified 3D model.
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公开(公告)号:US20230342507A1
公开(公告)日:2023-10-26
申请号:US18305276
申请日:2023-04-21
Applicant: DASSAULT SYSTEMES
Inventor: Nicolas BELTRAND
CPC classification number: G06F30/10 , G06T17/00 , G06T7/10 , G06V10/82 , G06T2207/20081
Abstract: A computer-implemented method of 3D reconstruction of at least one real object comprising an assembly of parts. The 3D reconstruction method includes obtaining a neural network configured for generating a 3D primitive CAD object based on an input depth image, obtaining a natural image and a depth image representing the real object, segmenting the depth image based at least on the natural image, each segment representing at most a respective part of the assembly, and applying the neural network to each segment.
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公开(公告)号:US20220036563A1
公开(公告)日:2022-02-03
申请号:US17384299
申请日:2021-07-23
Applicant: DASSAULT SYSTEMES
Inventor: Nicolas BELTRAND , Mourad BOUFARGUINE , Vincent GUITTENY
Abstract: A computer-implemented method for segmenting an object in at least one image acquired by a camera including computing an edge probabilities image based on the image, said edge probabilities image comprising, for each pixel of the image, the probability that said pixel is an edge, computing a segmentation probabilities image based on the image (IM), said segmentation probabilities image comprising, for each pixel of the image (IM), the probability that said pixel belongs to the object (OBJ), and computing a binary mask of the object based on the edge probabilities image and based on the segmentation probabilities image.
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