159 results about "3d shapes" patented technology

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 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.

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.

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 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.

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.

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.

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.

A technique disclosed herein creates a 3D shape model with a higher level of detail based on multiple different 3D shape models. Multiple 3D shape models for the same object are obtained and the likelihood (first likelihood) of each of polygons constituting each of the obtained 3D shape models is calculated. Using estimated skeleton data, the multiple 3D shape models with different poses are transformed into the same pose. Then, scale conversion is performed on the pose-transformed 3D shape models containing the pose-transformed skeleton data. The likelihood (second likelihood) of polygons in each certain subregion is calculated from the calculated likelihoods (first likelihoods) of the polygons. Subregions with the highest likelihoods (second likelihoods) of the polygons are extracted from the multiple 3D shape models, and combined to create a single 3D shape model.

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.

The present application relates to a method for preparing skeletal muscle organoids, comprising the steps of: inducing paraxial mesoderm stem cells (PMSCs) by directly differentiating human pluripotent stem cells (hPSCs); forming the paraxial mesoderm stem cells in a 3D shape, and then culturing same in a medium; inducing the proliferation of the paraxial mesoderm stem cells; and inducing the maturation of the paraxial mesoderm stem cells.

Systems and methods are provided for implementing a multi-stage, ML model training process for autonomous or semi-autonomous driving. The multi-stage ML model training process comprises (1) 2D and 3D supervised losses during a synthetic data ML model training, (2) 2D supervised on real-world data, and (3) 3D self-supervised losses on real-world data. The improved ML training process may not rely on 3D object recognition with real-world 3D labeled data. Once the ML model is trained, in some examples, the trained ML model can implement an inference process to predict the 3D shape, size, and 6D pose of objects within a single image, operate at a category level, and eliminate the need for computer-aided design (CAD) models during inference.

The present application belongs to the technical field of computer vision three-dimensional reconstruction, and specifically relates to a semi-supervised single-view 3D object reconstruction method. A small amount of labeled samples are used to train a neural network, and then the trained neural network is used to generate pseudo labels for unlabeled samples and guide the training of the unlabeled samples. At the same time, the present application proposes that a discriminator scores the quality of the generated pseudo labels, and limits the bias of low-quality pseudo labels on model training. In addition, the present application proposes a prototype shape prior module based on an attention mechanism, which serves as a bridge between images and 3D shapes, reduces the difference between the two modalities, and provides shape prior for the neural network, ensuring that the reconstructed 3D shape is natural. Compared with the current mainstream method in the industry, the present application is more accurate in three-dimensional reconstruction of a single image under the condition that the amount of labeled data is very small, and the generated 3D shape is more realistic and natural.

System, methods, and other embodiments described herein relate to single-shot multi-object three-dimensional (3D) shape reconstruction and categorical six-dimensional (6D) pose and size estimation. In one embodiment, a method includes inferring a heatmap based upon a feature pyramid, where the feature pyramid is generated based upon a red green blue depth (RGB-D) image that includes objects. The method further includes sampling a 3D parameter map at locations corresponding to peaks in the heatmap, where the 3D parameter map is inferred based upon the feature pyramid, and where the locations include latent shape codes, 6D poses, and one-dimensional (1D) scales. The method further includes generating point clouds based upon the latent shape codes, the 6D poses, and the 1D scales.

The utility model relates to the technical field of medical instruments, in particular to a light-weight three-dimensional (3D) conjoined tension-free inguinal hernia repair patch which comprises a patch body and a placing box used for storing the patch body, the patch body is of an axial symmetry structure and has a certain curvature, a plurality of large meshes are formed in the patch body, and the large meshes are arranged in the placing box. Large meshes are formed in the patch body, the porosity of the large meshes is the same, anchoring holes are formed in the periphery of the patch body, salient points are designed on the surface of the patch body, and a marking structure is further arranged on the patch body. The patch body which is in the axial symmetry shape and has the curvature is beneficial for adapting to anatomical differences of different patients to be cut, the 3D shape better conforms to the human groin structure, and placement is facilitated; a large mesh structure is arranged, so that the patch body is lighter; the hernia repair patch solves the problems that an existing common hernia repair patch is poor in fitting degree during use, inconvenient to store properly and prone to being infected by the external environment.

A first layer depth map generation unit (131) (distance acquisition unit) of an encoding apparatus (40a) (information processing apparatus) acquires a first distance (d1) between a projection point (Q) and a first point (P1) based on a 3D shape of a surface of a subject (90), a straight line extending from the projection point (Q) to the subject (90) contacts the subject (90) at the first point. A second layer depth map generation unit (132) (distance acquisition unit) acquires a second distance (d2) between the projection point (Q) and a second point (P2) based on the 3D shape of the surface of the subject (90), a straight line extending from the first point (P1) and into an interior of the subject (90) comes out of the subject (90) at the second point.

An organic interface converting data into tangible 3D shapes using programmable materials. It includes an interaction point with multiple surfaces and a projection module, all coordinated by a computing device for data transmission and reception. Data streams carry computer-readable code interpreted by the projection module to reorient surfaces, thereby materializing the data in three-dimensional space. The interface allows tactile input via human touch generating electrical currents that alter surface properties like position and smoothness. It also responds to audible frequencies and can receive data from secondary computing devices. Using a computing device, users can create 3D objects through data transmission to these responsive surfaces. The interface supports user interactions through touch, voice commands, and digital inputs from devices such as smartphones or tablets. Users have the flexibility to adjust the interface's resolution and response rate to tailor their interaction experience.

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

1. Name of the product in this design: Laundry detergent pods (3D bottom with 4 windmill-shaped beads). 2. Purpose of this design: For washing clothes. 3. The key design feature of this product is its shape. 4. The picture or photo that best illustrates the design points: Stereoscopic drawing 1.

Methods and systems are described for developing a sizing system by classifying and selecting prototypes, which can be considered as the most suitable fitting models. Once the prototypes are classified and selected, recommendations for sizing of a target body part can be issued.

This disclosure aims to make it possible to correct the displacement of the central axis of a tubular body caused by deformation of the tubular body. [Solution] This disclosure provides an analysis device that acquires measurement data of the surface shape of a target to be measured, calculates the longitudinal central axis of a tubular body in the target to be measured using the measurement data, and corrects the deviation of the central axis of the tubular body using information other than the tubular body obtained from the measurement data.

Techniques for generating a stylized drawing of three-dimensional (3D) shapes using neural networks are disclosed. A processing device generates a set of vector curve paths from a viewpoint of a 3D shape; extracts, using a first neural network of a plurality of neural networks of a machine learning model, surface geometry features of the 3D shape based on geometric properties of surface points of the 3D shape; determines, using a second neural network of the plurality of neural networks of the machine learning model, a set of at least one predicted stroke attribute based on the surface geometry features and a predetermined drawing style; generates, based on the at least one predicted stroke attribute, a set of vector stroke paths corresponding to the set of vector curve paths; and outputs a two-dimensional (2D) stylized stroke drawing of the 3D shape based at least on the set of vector stroke paths.

Embodiments are described for a graphic segmentation device comprising a memory and at least one processor coupled to the memory. The at least one processor is configured to receive point cloud data that represents a plurality of 3D objects and select one or more 3D volumes that segment a 3D object out of the plurality of 3D objects. Each of the one or more 3D volumes includes coordinates forming a 3D shape. The at least one processor is further configured to transmit a volume report to a graphic segmentation server, wherein the volume report includes the one or more 3D volume.

The invention relates to the field of three-dimensional mold pressing processes, and discloses a 3D mold pressing edge sealing process which comprises the following steps that multiple layers of materials are cut and stacked, and positioning holes are punched in the peripheral edge positions; the prepared composite material is placed on the lower die, the positioning area on the peripheral edge of the composite material is in positioning fit with the positioning part on the peripheral edge of the top of the lower die, and the composite material is placed above the anti-skid part on the top of the positioning part; the upper die moves downwards, the middle die firstly abuts against the positioning area of the composite material, the positioning area is pressed to form a 3D shape, the upper die continues to move downwards, the die pressing convex die of the upper die and the die pressing concave cavity of the lower die are subjected to die pressing forming, and the composite material with the 3D structure on the whole is formed; and the first edge sealing part of the upper mold and the second edge sealing part of the lower mold are subjected to mold pressing to form an edge sealing area with a 3D shape. The method has the advantages that sewing and edge sealing are not needed, the machining precision of a product with a precise 3D structure is high, and the method is suitable for a 3D mask and a 3D mold cup.

We provide the system. [Solution] A depth measurement means for acquiring three-dimensional shape data, A chat interface that receives user requests in natural language, A generation means for automatically generating a 3D model file based on the aforementioned 3D shape data and the aforementioned natural language request, A search method that searches for and presents existing products similar to the generated 3D model, A system that includes this.

Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures using generative design processes, where the three dimensional (3D) models of the physical structures are produced in accordance with a design criterion that limits a minimum thickness of the generatively designed 3D models, include: obtaining a design space for an object to be manufactured and one or more design criteria including a thickness constraint; iteratively modifying a generatively designed 3D shape of the modeled object in the design space in accordance with the one or more design criteria, including measuring a current thickness for the 3D shape using an overall relationship of a volume of the 3D shape with respect to a surface area of the 3D shape; and providing the generatively designed model for use in manufacturing the physical structure using one or more computer-controlled manufacturing systems.