公开(公告)号：US20200210845A1

公开(公告)日：2020-07-02

申请号：US16727413

申请日：2019-12-26

Applicant: DASSAULT SYSTEMES

Inventor： Fernando Manuel SANCHEZ BERMUDEZ ,  Eloi MEHR

IPC: G06N3/08 ,  G06N5/04 ,  G06N20/10 ,  G06F30/27 ,  G06F30/23 ,  G06T17/20

Abstract: The disclosure notably relates to computer-implemented method for learning a neural network configured for inference, from a freehand drawing representing a 3D shape, of a solid CAD feature representing the 3D shape. The method includes providing a dataset including freehand drawings each representing a respective 3D shape, and learning the neural network based on the dataset. The method forms an improved solution for inference, from a freehand drawing representing a 3D shape, of a 3D modeled object representing the 3D shape.

公开(公告)号：US20230418986A1

公开(公告)日：2023-12-28

申请号：US18341933

申请日：2023-06-27

Applicant: DASSAULT SYSTEMES

Inventor： Lucas BRIFAULT ,  Ariane JOURDAN ,  Eloi MEHR

IPC: G06F30/12

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.

公开(公告)号：US20220292352A1

公开(公告)日：2022-09-15

申请号：US17691703

申请日：2022-03-10

Applicant: DASSAULT SYSTEMES

Inventor： Ariane JOURDAN ,  Eloi MEHR

IPC: G06N3/08 ,  G06T17/20 ,  G06T9/00 ,  G06T7/11

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.

公开(公告)号：US20200285907A1

公开(公告)日：2020-09-10

申请号：US16879507

申请日：2020-05-20

Applicant: Dassault Systemes

Inventor： Eloi MEHR ,  Andre LIEUTIER

IPC: G06K9/62 ,  G06K9/66 ,  G06K9/00 ,  G06N3/08 ,  G06N3/04 ,  G06T7/30 ,  G06T3/00 ,  G06F30/00

Abstract: A computer-implemented method for learning an autoencoder notably is provided. The method includes obtaining a dataset of images. Each image includes a respective object representation. The method also includes learning the autoencoder based on the dataset. The learning includes minimization of a reconstruction loss. The reconstruction loss includes a term that penalizes a distance for each respective image. The penalized distance is between the result of applying the autoencoder to the respective image and the set of results of applying at least part of a group of transformations to the object representation of the respective image. Such a method provides an improved solution to learn an autoencoder.

公开(公告)号：US20210264079A1

公开(公告)日：2021-08-26

申请号：US17185795

申请日：2021-02-25

Applicant: DASSAULT SYSTEMES

Inventor： Eloi MEHR ,  Ariane JOURDAN

IPC: G06F30/23 ,  G06F30/27 ,  G06N3/04 ,  G06F17/11

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.

公开(公告)号：US20200250540A1

公开(公告)日：2020-08-06

申请号：US16727035

申请日：2019-12-26

Applicant: DASSAULT SYSTEMES

Inventor： Eloi MEHR

IPC: G06N3/08 ,  G06N20/00 ,  G06T17/20 ,  G06T7/55

Abstract: The disclosure notably relates to a computer-implemented method of machine-learning. The method includes obtaining a dataset including 3D modeled objects which each represent a respective mechanical part. The dataset has one or more sub-datasets. Each sub-dataset forms at least a part of the dataset. The method further includes, for each respective sub-dataset, determining a base template and learning a neural network configured for inference of deformations of the base template each into a respective 3D modeled object. The base template is a 3D modeled object which represents a centroid of the 3D modeled objects of the sub-dataset. The learning includes a training based on the sub-dataset. This constitutes an improved method of machine-learning with a dataset including 3D modeled objects which each represent a respective mechanical part.

公开(公告)号：US20200210636A1

公开(公告)日：2020-07-02

申请号：US16727338

申请日：2019-12-26

Applicant: DASSAULT SYSTEMES

Inventor： Fernando Manuel SANCHEZ BERMUDEZ ,  Eloi MEHR

IPC: G06F30/27 ,  G06F30/10

Abstract: The disclosure notably relates to a computer-implemented method for forming a dataset configured for learning a neural network. The neural network is configured for inference, from a freehand drawing representing a 3D shape, of a solid CAD feature representing the 3D shape. The method includes generating one or more solid CAD feature includes each representing a respective 3D shape. The method also includes, for each solid CAD feature, determining one or more respective freehand drawings each representing the respective 3D shape, and inserting in the dataset, one or more training samples. Each training sample includes the solid CAD feature and a respective freehand drawing. The method forms an improved solution for inference, from a freehand drawing representing a 3D shape, of a 3D modeled object representing the 3D shape.

公开(公告)号：US20240135733A1

公开(公告)日：2024-04-25

申请号：US18478685

申请日：2023-09-29

Applicant: DASSAULT SYSTEMES

Inventor： Lucas BRIFAULT ,  Eloi MEHR

IPC: G06V20/64 ,  G06T7/543

CPC classification number: G06V20/64 ,  G06T7/543 ,  G06T2207/20076

Abstract: A computer-implemented method including obtaining a mesh representing a segment of an outer surface of a portion of a mechanical part. The method further including determining curves over the mesh that each follows maximal curvature directions of the mesh, fitting each curve with a respective circle, thereby obtaining a set of circles, and calculating a value of one or more statistics of the set of circles. The method then detects whether the mesh is a fillet or not as a function of the value of the one or more statistics.

公开(公告)号：US20230036219A1

公开(公告)日：2023-02-02

申请号：US17949823

申请日：2022-09-21

Applicant: DASSAULT SYSTEMES

Inventor： Serban Alexandru STATE ,  Eloi MEHR ,  Yoan SOUTY

IPC: G06T17/20 ,  G06F30/23 ,  G06F30/17 ,  G06T5/00

Abstract: A computer-implemented method for 3D reconstruction including obtaining 2D images and, for each 2D image, camera parameters which define a perspective projection. The 2D images all represent a same real object. The real object is fixed.
The method also includes obtaining, for each 2D image, a smooth map. The smooth map has pixel values, and each pixel value represents a measurement of contour presence. The method also includes determining a 3D modeled object that represents the real object. The determining iteratively optimizes energy. The energy rewards, for each smooth map, projections of silhouette vertices of the 3D modeled object having pixel values representing a high measurement of contour presence. This forms an improved solution for 3D reconstruction.

公开(公告)号：US20210201587A1

公开(公告)日：2021-07-01

申请号：US17138259

申请日：2020-12-30

Applicant: DASSAULT SYSTEMES

Inventor： Eloi MEHR ,  Vincent GUITTENY

IPC: G06T19/00 ,  G06T7/73 ,  G06K9/62

Abstract: A computer-implemented method of augmented reality includes capturing the video flux with a video camera, extracting, from the video flux, one or more 2D images each representing the real object, and obtaining a 3D model representing the real object. The method also includes determining a pose of the 3D model relative to the video flux, among candidate poses. The determining rewards a mutual information, for at least one 2D image and for each given candidate pose, which represents a mutual dependence between a virtual 2D rendering and the at least one 2D image. The method also includes augmenting the video flux based on the pose. This forms an improved solution of augmented reality for augmenting a video flux of a real scene including a real object.