245 results about "3d shapes" patented technology

A computer-implemented method for designing a 3D modeled object representing a product to be manufactured, the designing method including, by a computer system, displaying simultaneously a 3D shape representation of the 3D modeled object, and a 2D block representation of the 3D modeled object. The method also comprises by a user interacting graphically with the 2D block representation, performing a selection of one or more block nodes among the at least one block node, upon user-action, adding to the 2D block representation a block node representing a respective operator of the subset, and automatically determining a respective arc between the output connector of each selected block node and a respective input connector of the added block node. The disclosure improves ergonomics.

The invention discloses a multi-scale point cloud pre-training method for sampling from top to bottom, equipment and a medium. According to the method, through a U-Net type asymmetric encoder-decoder architecture and in combination with a multi-scale mask, the extraction capability of local features and global information of point cloud data is enhanced. According to the method, firstly, input point cloud data is subjected to multi-scale division and mask processing, then multi-scale features are extracted through an encoder, a masked point cloud area is reconstructed through a decoder, and a masked local point cloud block is recovered through a linear projection layer. According to the invention, the problem of multi-scale information leakage in the prior art is effectively avoided, and the point cloud data processing precision is improved. After self-supervised pre-training, the model shows excellent performance in a plurality of downstream tasks, especially in applications such as 3D shape classification, object detection and partial segmentation. The method has the advantages of high robustness and wide application prospect.

The invention discloses a compressor crankshaft high-precision 3D shape detection method based on laser vision, belongs to the technical field of precision measurement and intelligent manufacturing, and aims to solve the problems existing in crankshaft detection. The method comprises the following steps: step 1, scanning a compressor crankshaft in a non-contact manner by adopting a three-coordinate motion platform carrying a line laser contourgraph to obtain an original three-dimensional point cloud; 2, carrying out the preprocessing of the original three-dimensional point cloud through employing adaptive radius filtering and minimum point constraint voxel filtering; step 3, realizing pin hole position degree detection based on an improved RANSAC algorithm and two-dimensional boundary clustering, and fitting an end surface excircle and a pin hole circle to obtain the pin hole position degree; and step 4, realizing pin-end face perpendicularity detection through coarse registration and weighted ICP fine registration. The method is used for detecting the 3D morphology of the crankshaft.

The document relates to a tool for producing a 3D molded product from a pulp slurry, comprising a pair of molds having respective product faces, that are configured to face each other and to press a pulp layer therebetween, said product faces providing a 3D shape for molding the 3D molded product, said product faces presenting a respective outer product face edge, defining an outermost limit of a forming area of mold. At least one of the product faces, as seen from the product face edge and inwardly towards a center of gravity of the product face, presents an outer zone (Z1) having effectively no porosity, and an inner zone (Z4) having a porosity of 40-75%, wherein a first intermediate zone (Z2) is arranged between the outer zone (Z1) and the inner zone (Z4), and has a porosity that is greater than that of the outer zone (Z1) and less than that of the inner zone (Z4).

The invention relates to the technical field of optical measurement, in particular to a complex reflective object surface reconstruction method and system based on multi-system point cloud fusion, and the method comprises the steps: carrying out the joint calibration of the spatial relation among a camera, a projector and an LCD screen; projecting to a target object based on a projection grating phase method and a phase deflection operation path, and collecting structured light patterns of the two through a camera; phase solving is carried out on the structured light pattern collected by the camera, and a three-dimensional reconstruction result is obtained in combination with the joint calibration information; and world coordinate system matching and point cloud fusion are carried out on the three-dimensional reconstruction result based on the joint calibration information, and the three-dimensional morphology of the target object is generated. According to the method, the problems that in diffuse reflection reconstruction, patterns projected by a projector cannot be comprehensively collected due to exposure and height and gradient ambiguity cannot be solved by a monocular phase deflection technology in high reflection can be solved complementarily, high reflection and diffuse reflection objects can be solved, a complete reconstructed object can be obtained, and the reconstruction precision is improved.

The invention belongs to the technical field of refraction detection, and particularly relates to a human eye dynamic refraction detection method based on a three-dimensional phase deflection method. The method comprises the following steps: S1, based on a three-dimensional phase deflection imaging system and an iterative representation integral algorithm, obtaining a 3D shape of a to-be-detected human eye in place in real time; s2, on the basis of the 3D shape of the to-be-detected human eye, the current staring direction of the to-be-detected human eye is obtained in real time in place by combining a ray tracing method; s3, establishing a refractive imaging system, and obtaining a diopter value of the to-be-measured human eye in the current staring direction in real time in place based on the refractive imaging system; and S4, fitting different staring directions of the to-be-detected human eyes and the dynamic numerical curve of the diopter values in the corresponding staring directions to realize human eye dynamic refraction detection. According to the method, an accurate treatment scheme can be accurately provided for the ametropia patient in a real scene, and guidance can be provided in the aspect of personalized customization of the spectacle lenses.

A system and method directed to detecting placement of a medical device within a patient body, the system including a medical device including a multi-core optical fiber having a plurality of core fibers. Each of the plurality of core fibers can include a plurality of sensors each configured to reflect a light signal having an altered characteristic due to strain experienced by the multi-core optical fiber. The system can further include logic configured to determine a 3D shape of the medical device in accordance with the strain of the optical fiber. The logic can be configured to define a reference plane for the 3D shape and render an image of the 3D shape on a display of the system in accordance with the reference plane.

A method and a computing system including a memory and a processor learn a content generation model. The method may include preparing a training data set including a plurality of pairs of contents and captions, learning a first machine learning model to restore the contents from a low-dimensional latent code, learning a second machine learning model to output a latent code for a text embedding by learning relationship between text embeddings and latent codes of the pairs of the contents and the captions, and combining the first machine learning model and the second machine learning model. The content is implicit data which is function-based 3D shape data.

A robot interference checking motion planning technique using point sets. The technique uses CAD models of robot arms and obstacles and converts the CAD models to 3D point sets. The 3D point set coordinates are updated at each time step based on robot and obstacle motion. The 3D points are then converted to 3D grid space indices indicating space occupied by any point on any part. The 3D grid space indices are converted to 1D indices and the 1D indices are stored as sets per object and per time step. Interference checking is performed by computing an intersection of the 1D index sets for a given time step. Swept volumes are created by computing a union of the 1D index sets across multiple time steps. The 1D indices are converted back to 3D coordinates to define the 3D shapes of the swept volumes and the 3D locations of any interferences.

The invention relates to the technical field of weld joint detection, and provides a visual intelligent weld joint detection device and method, and the detection method comprises the steps: obtaining a 2D image of a weld joint; weld joint 3D shape data are obtained, and weld joint point cloud data are generated; generating a training data set according to the welding seam 2D image and the welding seam point cloud data; constructing a neural network model, and training the neural network model through the training data set; performing intelligent detection on the weld seam image according to the trained neural network model; wherein a loss function of the neural network model comprises a 2D positioning loss item, a classification task loss item and a 3D frame regression loss item. According to the method, by obtaining the loss function including the 2D positioning loss item, the classification task loss item and the 3D frame regression loss item, multi-task collaborative optimization can be realized, classification robustness, 2D positioning precision and 3D geometric reconstruction capability are considered, and the method is suitable for scene requirements of high precision and multi-modal fusion in industrial detection.

The invention discloses an insulator real-time rendering method, system and device and a medium. The method comprises the steps of obtaining point cloud data of a transformer substation insulator to be rendered; and inputting the point cloud data of the transformer substation insulator to be rendered into a trained insulator real-time rendering model represented by an implicit 3D shape to obtain a rendered insulator, the insulator real-time rendering model represented by the implicit 3D shape comprises a sparse voxel field construction module, a feature vector query and interpolation module and a light tracing and rendering module, and the method, the system, the equipment and the medium can realize real-time rendering of the insulator, and have the characteristics of excellent detail representation, rendering efficiency and resource consumption performance.

In various examples, image-based three-dimensional occupant evaluation for in-cabin monitoring systems and applications is provided. The evaluation function may determine a 3D representation of an occupant of the machine by evaluating sensor data containing image frames from the optical image sensor. The 3D representation may include at least one characteristic (e.g., 3D pose and / or 3D shape) representing the size of the occupant, which may be used to derive other characteristics, such as, but not limited to, weight, height, and / or age. The first processing path may generate a representation of one or more features corresponding to at least a portion of the occupant based on the optical image data, and the second processing path may determine a depth corresponding to the one or more features based on depth data derived from the optical image data and truth-valued depth data corresponding to the machine interior.

In various examples, a deep three-dimensional (3D) conditional generative model is implemented that can synthesize high resolution 3D shapes using simple guides—such as coarse voxels, point clouds, etc.—by marrying implicit and explicit 3D representations into a hybrid 3D representation. The present approach may directly optimize for the reconstructed surface, allowing for the synthesis of finer geometric details with fewer artifacts. The systems and methods described herein may use a deformable tetrahedral grid that encodes a discretized signed distance function (SDF) and a differentiable marching tetrahedral layer that converts the implicit SDF representation to an explicit surface mesh representation. This combination allows joint optimization of the surface geometry and topology as well as generation of the hierarchy of subdivisions using reconstruction and adversarial losses defined explicitly on the surface mesh.

A 3D shape matching method and a 3D shape matching device based on 3D local feature description using SGHs are provided. In the method, the spherical neighborhood of the feature point is not only divided based on space but also divided based on geometry, the spherical neighborhood of the feature point is not only divided based on the radial direction and the azimuth respectively but also divided based on the elevation, and the spherical neighborhood of the feature point is not only divided based on the deviation angle deviating from the z axis but also divided based on the deviation angle deviating from the x axis. When the deviation angle deviating from the z axis of the spherical neighborhood is divided, the deviation angle is divided more densely where it is closer to the positive direction of the z axis.

The invention relates to the technical field of optical fiber communication device detection, and provides an optical fiber connector end face 3D shape detection method and system, and the method comprises the steps: obtaining a multi-step phase shift interference image sequence of an optical fiber connector end face; performing interface segmentation on the multi-step phase shift interference image sequence by adopting a fiber core boundary detection network based on radial gradient perception to obtain interface position data; based on the interface position data and the multi-step phase shift interference image sequence, performing phase unpacking by adopting a dual-coordinate system fusion phase unpacking algorithm to obtain initial phase data; performing global reconstruction on the initial phase data by adopting a regional confidence coefficient weighted reconstruction algorithm to obtain global phase field data; performing spherical parameter fitting on the global phase field data by adopting an IEC (International Electrotechnical Commission) standard constraint hierarchical particle swarm optimization algorithm to obtain spherical geometric parameters; and generating a 3D shape detection result of the end face of the optical fiber connector according to the spherical geometric parameters. According to the invention, the precision and reliability of 3D shape detection of the end face of the optical fiber connector are improved.

A computer-implemented method, computing device, system and computer program product for assisting positioning of a tool (5) with respect to a specific body part (202) of a patient (200) comprising: receiving intraoperative imaging data (ID) comprising 2D images capturing the specific body part (202) from a plurality of perspectives and 2D image(s) capturing at least a part of the tool (5) from at least one perspective; reconstructing an anatomical 3D shape (AS) of the specific body part (202) using an artificial-intelligence based algorithm corresponding to the specific body part (202) based on the intraoperative imaging data (ID) and data indicative of perspectives of 2D images; estimating a current position (5c) of the tool (5) with respect to the anatomical 3D shape (AS) based on the intraoperative imaging data (ID); and generating positioning guidance data (GD) comprising the estimated current position (5c) of the

A method of measuring a 3D shape of an object comprising a target semi-transparent surface, the method comprising the steps of: with a projector, projecting a first light signal having a predetermined pattern and a predetermined frequency from at least one projector column towards at least one location on a scene; with an image capture device, receiving a second light signal from the at least one location of the scene at an image capture device pixel; measuring an intensity signal received at the image capture device pixel; with the measured intensity signal, generating a correspondence map between the at least one projector column illuminating the at least one location of the scene and the image capture device pixel with coordinates receiving the light signal from the at least one location of the scene; and with the correspondence map, determining 3D coordinates of the at least one location of the scene.

The invention discloses a numerical control machining process generation method based on a PVFNN neural network, and the method mainly comprises the steps: 1) data preprocessing: collecting and processing the 3D shape, material and quality information of a part; 2) constructing and segmenting a data set to form a training, verification and test set; 3) constructing a PVFNN neural network model, integrating a 3D convolutional neural network, a point cloud neural network and a full connection network, and realizing feature fusion through a feature fusion layer and an MLP; 4) performing model training and verification, using a training set to train the model, and using a test set to evaluate performance; 5) process generation: performing model processing on new part information to generate a processing process; the method is used for automatically learning the capability of the discrete manufacturing process from design and manufacturing data, the accuracy and efficiency of numerical control machining process generation are improved, and the problem that in the prior art, due to the influence of manufacturing process capability knowledge and manufacturing experience, a user often cannot select the optimal manufacturing process is solved.

One embodiment of the present invention sets forth a technique for performing style transfer. The technique includes determining a distribution associated with a plurality of style codes for a plurality of three-dimensional (3D) shapes, where each style code included in the plurality of style codes represents a difference between a first 3D shape and a second 3D shape, and where the second 3D shape is generated by applying one or more augmentations to the first 3D shape. The technique also includes sampling from the distribution to generate an additional style code and executing a trained machine learning model based on the additional style code to generate an output 3D shape having style-based attributes associated with the additional style code and content-based attributes associated with an object. The technique further includes generating a 3D model of the object based on the output 3D shape.

One embodiment of the present invention sets forth a technique for generating a geometry for a shape. The technique includes inputting, into a machine learning model, (i) a noise sample and (ii) one or more conditioning inputs. The technique also includes generating, via execution of the machine learning model based on the noise sample and the one or more conditioning inputs, a two-dimensional (2D) position map associated with the shape. The technique further includes generating a three-dimensional (3D) geometry for the shape based on the 2D position map.

The invention discloses a multi-particle three-dimensional shape reconstruction method based on projection consistency. According to the method, a three-angle laser interference particle imaging system is used for collecting out-of-focus images of three visual angles, a center M * N pixel range is cut to obtain an out-of-focus speckle image, phase recovery algorithm reconstruction is carried out, a two-dimensional particle shape is obtained, a gray threshold value above 70 is set to be a target contour area, binarization segmentation is carried out, and a target contour image is obtained. And smoothing the target contour area. And carrying out three-dimensional space projection on contours of the four candidate results in Matlab, generating a three-dimensional structure in an intersection region, re-projecting the three-dimensional structure to each view angle, calculating an error S between a re-projected image and an original input projection, and selecting a final reconstruction result with the minimum S. According to the method, through systematic iterative optimization and an error evaluation mechanism, trivial fuzzy interference in a phase recovery process is effectively eliminated, and high-precision reconstruction of a multi-particle three-dimensional shape is realized.

An electronic device for providing an avatar is provided. The electronic device includes memory storing one or more computer programs, and one or more processors communicatively coupled to the memory, wherein the one or more computer programs include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the electronic device to obtain a plurality of raw textures by matching a three-dimensional (3D) shape related to a user face to a two-dimensional (2D) plane, perform tone-matching for smoothing each of skin tones of the plurality of raw textures based on an average of the skin tones of the plurality of raw textures, obtain a plurality of texture segments by splitting at least one of a plurality of tone-matched raw textures for each feature area in a face, obtain a combined texture by combining a plurality of texture segments selected by a user input from among the obtained plurality of texture segments, and obtain an avatar representing the user face in a 3D shape based on the combined texture.

Disclosed is an apparatus for predicting a 3D structure of a patient-tailored implant, including a memory that stores at least one instruction for predicting the 3D structure of the patient-tailored implant, and a processor that executes an operation according to the instruction, wherein the processor models a correlation between a 2D meniscus shape and a 3D meniscus shape, and predicts the 3D meniscus shape based on 3D shape features derived from modeling results.

A system and method directed to detecting placement of a medical device within a patient body, the system including a medical device including an optical fiber having core fibers. Each of the one or more core fibers can include a plurality of sensors each configured to reflect a light signal having an altered characteristic due to strain experienced by the optical fiber. The system can further include logic configured to determine a 3D shape of the medical device in accordance with the strain of the optical fiber. The logic can be configured to define a reference plane for the 3D shape and render an image of the 3D shape on a display of the system in accordance with the reference plane.

The disclosure notably relates to a computer-implemented method for designing a 3D modeled object representing a product to be manufactured. The designing method comprises, by a computer system, displaying simultaneously a 3D shape representation of the 3D modeled object, and a 2D block representation of the 3D modeled object. The designing method also comprises by a user interacting graphically with the 2D block representation, performing a selection, among the at least one block node, of one or more connectors. The designing method also comprises using a pre-trained machine-learning function for prediction of one or more operators among the predetermined set of operators. The disclosure improves ergonomics.

One embodiment of the present invention sets forth a technique for training a machine learning model on a geometry generation task. The technique includes generating, via execution of a diffusion model, a first set of training output corresponding to a first set of three-dimensional (3D) geometries based on a first set of conditioning inputs associated with a first conditioning mode, and training the diffusion model based on a first set of loss values associated with the first set of training output. The technique further includes generating, via execution of the diffusion model and a first adapter model, a second set of training output corresponding to a second set of 3D geometries based on a second set of conditioning inputs associated with a second conditioning mode, and training the first adapter model based on a second set of loss values associated with the second set of training output.

The embodiment of the invention relates to the technical field of costume design, and particularly discloses a costume design method and system based on 3D modeling. According to the embodiment of the invention, 3D shape data of a target user is acquired; acquiring historical clothing data, and performing design matching selection; performing model creation and matching rendering; interactive display of costume design is carried out on the target user, and interactive design operation is received; and performing supplementary rendering and naked-eye 3D scene processing, and generating and displaying a costume design naked-eye 3D video. 3D shape data and historical clothing data of a target user can be obtained, design matching selection, model creation and matching rendering are performed, interactive design operation of the target user is received, supplementary rendering and naked eye 3D scene processing are performed on a 3D matching model, customized clothing design can be performed according to the accurate shape data of the user, and the user experience is improved. And the garment design can be displayed in authenticity, so that the interactivity and the fun of the garment design are enhanced.

A method for three-dimensional (3D) shape part segmentation includes obtaining two-dimensional (2D) predictions for part segmentation of a 3D shape, lifting the 2D predictions onto the 3D shape to obtain initial 3D part segmentation knowledge, processing the 3D shape using a 3D encoder to extract geometric features, performing a distillation process to refine the initial 3D part segmentation knowledge, and generating a final 3D shape part segmentation according to the refined 3D part segmentation knowledge and the geometric features.

The present invention relates to a cellulose-based 3D shaped substrate comprising natural cellulosic fibers and a non-fibrous cellulosic material; a method for preparing a cellulose-based 3D shaped substrate, the cellulose-based 3D shaped substrate comprising natural cellulosic fibers and a non-fibrous cellulosic material; a method of processing a cellulose-based 3D shaped substrate; and to the use of a cellulose-based 3D shaped substrate for packaging.

To provide a three-dimensional shape measuring device capable of reducing measurement errors and performing accurate measurements in pinhole array scanning using a confocal optical system. A three-dimensional shape measurement device according to one embodiment of the present invention is a three-dimensional shape measurement device using a confocal optical system, and includes at least an aperture plate on which a plurality of confocal apertures through which light from a light source passes are arranged two-dimensionally at a predetermined arrangement period, and an aperture plate displacement unit that displaces the aperture plate at a uniform speed in a predetermined direction perpendicular to the optical axis direction so as to change the relative positional relationship between the position of the object-side focusing point and the position of the object to be measured in the direction perpendicular to the optical axis direction. The three-dimensional shape measurement device controls the movement speed of the aperture plate, the rotation speed of the rotor, and the exposure time and exposure timing of the photodetector group so that the exposure time of the photodetector group coincides with the time it takes for the aperture plate to move a distance obtained by multiplying the predetermined arrangement period by an integer n greater than or equal to 2.