SKETCH-PROCESSING
    1.
    发明公开
    SKETCH-PROCESSING 审中-公开

    公开(公告)号:US20230306162A1

    公开(公告)日:2023-09-28

    申请号:US18176853

    申请日:2023-03-01

    CPC classification number: G06F30/23 G06V30/333 G06T11/203 G06T7/12 G06F30/17

    Abstract: A computer-implemented method for sketch-processing. The method including obtaining one or more input sketches and determining one or more output sketches from the one or more input sketches. Each output sketch is closed and manifold. The determining of the one or more output sketches includes constructing a set of manifold sketches including each manifold input sketch. The constructing of the set of manifold sketches includes, for each respective non-manifold input sketch, determining two or more respective manifold sketches based on at least one intra-sketch intersection of the respective non-manifold input sketch. The determining of the one or more output sketches includes combining each pair of manifold sketches of the constructed set that share at least two intersections, to form one or more closed and manifold sketches. The method forms an improved solution for sketch-processing.

    PROCESSING A CAD 3D MODEL OF A MECHANICAL PART

    公开(公告)号:US20220398356A1

    公开(公告)日:2022-12-15

    申请号:US17805406

    申请日:2022-06-03

    Abstract: A computed-implemented method for processing a computer-aided design 3D model of a mechanical part including a portion having a distribution of material. The method including obtaining the 3D model, the 3D model including a skin portion of the 3D model representing an outer surface of the portion of the mechanical part. The method further including processing the skin portion based on an extrusion-processing algorithm, where a transform of the skin portion is inputted to the algorithm. The transform represents an unfolding of the distribution of material of the portion.

    CAD FEATURE TREE OPTIMIZATION
    3.
    发明公开

    公开(公告)号:US20230418986A1

    公开(公告)日:2023-12-28

    申请号:US18341933

    申请日:2023-06-27

    CPC classification number: G06F30/12

    Abstract: The disclosure notably relates to a computer-implemented method for generating a CAD feature tree from a discrete geometrical representation of a mechanical product. The method comprises obtaining the discrete geometrical representation, and a set of CAD features. The method further comprises determining one or more sequences of CAD features from the set of CAD features by optimizing an objective function which rewards a fitting of the discrete geometrical representation by a candidate sequence, and penalizes a complexity of a candidate sequence, the complexity of a candidate sequence being a function of the candidate sequence that increases when adding a feature to the candidate sequence.

    MACHINE-LEARNING FOR 3D SEGMENTATION

    公开(公告)号:US20220292352A1

    公开(公告)日:2022-09-15

    申请号:US17691703

    申请日:2022-03-10

    Abstract: A computer-implemented method of machine-learning including obtaining a dataset of training samples. Each training sample includes a pair of 3D modeled object portions labelled with a respective value. The respective value indicates whether or not the two portions belong to a same segment of a 3D modeled object. The method further includes learning a neural network based on the dataset. The neural network takes as input two portions of a 3D modeled object representing a mechanical part and outputs a respective value. The respective value indicates an extent to which the two portions belong to a same segment of the 3D modeled object. The neural network is thereby usable for 3D segmentation. The method constitutes an improved solution for 3D segmentation.

    MATERIAL EXTRUSION DETECTION METHOD

    公开(公告)号:US20220382931A1

    公开(公告)日:2022-12-01

    申请号:US17664453

    申请日:2022-05-23

    Abstract: A computer-implemented method for material extrusion detection in a portion of a mechanical part having a distribution of material. The method includes obtaining a CAD 3D model of the mechanical part including a skin portion representing an outer surface of the portion of the mechanical part and an extrusion axis. The method further includes computing a ratio of an area of an orthogonal projection of the skin portion over an area of the skin portion. The method further includes determining whether or not the distribution of material is arranged as an extrusion based on the ratio and a ratio threshold. The outer surface is determined to be an extrusion surface when the ratio is lower than the ratio threshold. This forms an improved solution for processing a CAD 3D model of a mechanical part.

    DETERMINING A 3D MODELED OBJECT DEFORMATION

    公开(公告)号:US20210264079A1

    公开(公告)日:2021-08-26

    申请号:US17185795

    申请日:2021-02-25

    Abstract: Described is a computer-implemented method for determining a 3D modeled object deformation. The method comprises providing a deformation basis function configured for inferring a deformation basis of an input 3D modeled object. The method further comprises providing a first 3D modeled object. The method further comprises providing a deformation constraint of the first 3D modeled object. The method further comprises determining a second 3D modeled object which respects the deformation constraint. The determining of the second 3D modeled object comprises computing a trajectory of transitional 3D modeled objects between the first 3D modeled object and the second 3D modeled object. The trajectory deforms each transitional 3D modeled object by a linear combination of the result of applying the deformation basis function to the transitional 3D modeled object. The trajectory reduces a loss penalizing an extent of non-respect of the deformation constraint by the deformed transitional 3D modeled object.

    SEGMENTING A 3D MODELED OBJECT REPRESENTING A MECHANICAL PART

    公开(公告)号:US20220261512A1

    公开(公告)日:2022-08-18

    申请号:US17562406

    申请日:2021-12-27

    Abstract: A computer-implemented method for segmenting a 3D modeled object. The 3D modeled object represents a mechanical part. The method includes obtaining the 3D modeled object. The method further includes performing a hierarchical segmentation of the 3D modeled object. The hierarchical segmentation comprises a first segmentation. The first segmentation includes identifying, among surfaces of the 3D modeled object, first segments each corresponding to a simple geometric surface of the 3D modeled object. A simple geometric surface is a primitive exhibiting at least one slippable motion. The hierarchical segmentation includes then a second segmentation. The second segmentation includes identifying, among non-identified surfaces of the 3D modeled object, second segments each corresponding to a free-form surface of the 3D modeled object. This constitutes an improved method for segmenting a 3D modeled object representing a mechanical part.

    ADVERSARIAL 3D DEFORMATIONS LEARNING

    公开(公告)号:US20220245431A1

    公开(公告)日:2022-08-04

    申请号:US17646082

    申请日:2021-12-27

    Abstract: A computer-implemented method of machine-learning. The method includes obtaining a dataset of 3D modeled objects representing real-world objects. The method further includes learning, based on the dataset, a generative neural network. The generative neural network is configured for generating a deformation basis of an input 3D modeled object. The learning includes an adversarial training.

    METHOD FOR 3D SCANNING OF A REAL OBJECT

    公开(公告)号:US20220028100A1

    公开(公告)日:2022-01-27

    申请号:US17377014

    申请日:2021-07-15

    Abstract: A computer-implemented method for 3D scanning of a real object with a camera having a 3D position including receiving, from the camera, an image of the real object, displaying on a screen, in an augmented reality view, the image of the real object enclosed within a virtual 3D box and, superimposed to the real object, a virtual structure made of a set of planar tiles, and being anchored to the virtual 3D box, each tile corresponding to a predetermined pose of the camera, detecting that a tile is pointed at with the camera; acquiring, from the camera, a frame of the virtual 3D box, thereby validating said tile, said frame being a projection of the virtual 3D box on the image, iterating for different 3D positions of the camera, until a sufficient number of tiles is validated for scanning the real object, and implementing a 3D reconstruction algorithm with all captured frames.

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