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.

Abstract: 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. Each CAD feature includes an interior and a boundary, the boundary representing a surface covered by the feature and the interior representing a surface erased by the feature. The method further comprises determining an optimal sequence of CAD features from the set of CAD features providing an optimal surface covering of the discrete geometrical representation.

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.

Abstract: A computer-implemented method for CAD volume extrusion operator detection in a CAD 3D model representing a mechanical part. The method includes obtaining a segmentation of the CAD 3D model. The CAD 3D model includes a skin representing an outer surface of the mechanical part. The segmentation comprises segments each representing a skin portion. The method further includes iteratively grouping segments. Segments of a pair are grouped when: each segment of the pair is an extrusion surface and a union of the segments is an extrusion surface having a same extrusion axis as the segments, or each segment of the pair is an extrusion surface and one of the two segments is a closing plane for the other segment. The method further includes determining one or more CAD volume extrusion operators, each corresponding to a respective group.

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.

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.

Abstract: The disclosure notably relates to a computer-implemented method for generating a structured three-dimensional (3D) model from a mesh. The method includes obtaining a mesh that comprises faces, each face of the mesh including a normal and principal curvature values; computing a distribution of the principal curvatures values over the whole mesh by counting the number of occurrences of discretized curvature values; identifying in the computed distribution one or more dominant ranges of principal curvature values; for each identified dominant range, computing one or more regions of the mesh that includes faces belonging to the identified dominant range; for each computed region, detecting a primitive type by using the curvatures values of all faces of the region and identifying parameters of the detected primitive by using the mesh surface of the region.

Abstract: The disclosure notably relates to a computer-implemented method for extracting a feature tree from a mesh. The method includes providing a mesh, computing a geometric and adjacency graph of the provided mesh, wherein each node of the graph represents one region of the mesh and comprises a primitive type and parameters of the region, each connection between two nodes is an intersection between the respective surfaces of the regions represented by the two connected nodes. The method also includes instantiating for each node of the graph, a surface based on the identified primitive type and parameters of the region.

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.

Abstract: The disclosure notably relates to a computer-implemented method for extracting a feature tree from a mesh. The method includes providing a mesh, computing a geometric and adjacency graph of the provided mesh, wherein each node of the graph represents one region of the mesh and comprises a primitive type and parameters of the region, each connection between two nodes is an intersection between the respective surfaces of the regions represented by the two connected nodes. The method also includes instantiating for each node of the graph, a surface based on the identified primitive type and parameters of the region.

Abstract: The disclosure notably relates to a computer-implemented method for generating a structured three-dimensional (3D) model from a mesh. The method includes obtaining a mesh that comprises faces, each face of the mesh including a normal and principal curvature values; computing a distribution of the principal curvatures values over the whole mesh by counting the number of occurrences of discretized curvature values; identifying in the computed distribution one or more dominant ranges of principal curvature values; for each identified dominant range, computing one or more regions of the mesh that includes faces belonging to the identified dominant range; for each computed region, detecting a primitive type by using the curvatures values of all faces of the region and identifying parameters of the detected primitive by using the mesh surface of the region.