165 results about "3d surfaces" patented technology

In various examples, systems and methods are disclosed relating to geometry estimation and dynamic object rendering for vehicle environment visualization. In embodiments, the environment surrounding an ego-machine may be visualized by extracting one or more depth maps from image data, converting the depth map(s) into a 3D surface topology of the surrounding environment, and / or texturizing the detected 3D surface topology with image data. Dynamic objects such as moving vehicles or pedestrians may be detected and masked from a first pass of texturization. Rigid dynamic objects may be visualized by warping corresponding depth values using corresponding trajectories, inserting or fusing the resulting warped 3D representation of each such object into the (e.g., texturized) 3D surface topology, and texturizing the warped 3D representation of each object using corresponding image data. Non-rigid dynamic objects may be represented as flat 2D surfaces and texturized with corresponding image data.

The invention discloses depth-based vehicle environment visualization using generative AI. In various examples, systems and methods related to geometry estimation and dynamic object rendering for vehicle environment visualization are disclosed. The environment around the ego-vehicle may be visualized by extracting one or more depth maps from the image data, converting the depth maps to a 3D surface topology of the surrounding environment, and / or texturing the detected 3D surface topology with the image data. Dynamic objects may be detected and masked from a first pass of texturing. Rigid body dynamic objects may be visualized by warping a respective depth map using a respective trajectory, inserting or fusing the resulting warped 3D representation of each such object into a (textured) 3D surface topology, and texturing the warped 3D representation of each object using a respective image data. The non-rigid dynamic object may be represented as a flat 2D surface and textured with corresponding image data.

In various examples, systems and methods are disclosed relating to geometry estimation and dynamic object rendering for vehicle environment visualization. In embodiments, the environment surrounding an ego-machine may be visualized by extracting one or more depth maps from image data, converting the depth map(s) into a 3D surface topology of the surrounding environment, and / or texturizing the detected 3D surface topology with image data. Dynamic objects such as moving vehicles or pedestrians may be detected and masked from a first pass of texturization. Rigid dynamic objects may be visualized by warping corresponding depth values using corresponding trajectories, inserting or fusing the resulting warped 3D representation of each such object into the (e.g., texturized) 3D surface topology, and texturizing the warped 3D representation of each object using corresponding image data. Non-rigid dynamic objects may be represented as flat 2D surfaces and texturized with corresponding image data.

A Kaleidoscopic Geometric Vision Platform (KGVP) that transforms three-dimensional (3D) machine vision through an optical system that creates multiple virtual laser projectors from a single moving component. A spindle mirror mechanism (SMM) rotates a reflective surface to sweep collimated laser beams in circular patterns. These beams strike a series of kaleidoscopic mirror facets (KMFs) arranged concentrically around the SMM in a concave configuration. Each KMF redirects the rotating beam, creating a virtual projector with a distinct origin point and sweep direction. As the SMM completes one rotation, it generates N distinct laser trajectories (where N equals the number of KMFs), each sweeping from a different virtual origin point. Event-based cameras / sensors positioned strategically around the KMFs detect laser light reflected from object surfaces with microsecond precision. The KGVP triangulates 3D surface coordinates by determining correspondence between detected light and specific virtual projectors based on precise timing information.

The invention discloses an automobile part defect detection method based on multispectrum, and relates to the technical field of spectrum detection. According to the method, an optimal wave band is screened from a data source through spectral response discrimination, and the spectral texture difference between scratches and normal textures is enhanced; normal texture and suspected scratch areas are accurately divided through density clustering, a target area is focused, irrelevant data interference is reduced, and it is ensured that double-feature extraction is higher in pertinence. Further synchronously extracting texture gray level change features and 3D surface height depression features of the suspected area, and capturing dual attributes of two-dimensional texture anomaly and three-dimensional physical form depression of the scratch; and finally, through deviation calculation and relevance verification with a normal region reference feature, the abnormal degree of the double features is quantified, two types of abnormalities are ensured to correspond to the same physical region through spatial relevance, pseudo defects are eliminated, and the problem that scratches are difficult to identify based on texture gray level change and surface height depression in the prior art is solved.

Aspects of this technical solution can allocate one or more portions of a mesh in a three-dimensional (3D) space to one or more processing units associated with the one or more circuits, the mesh associated with a surface of an object in the 3D space, transform, by the one or more of the processing units, one or more of the portions of the mesh from the 3D space into corresponding second meshes in a two-dimensional (2D) space, segment, by the one or more of the processing units, according to a determination that a distortion of a portion of the mesh among the one or more of the portions of the mesh is below a threshold of parameterization, the portion of the mesh into two further portions of the mesh, where the further portions are among the one or more portions of the mesh, and generate, according to a determination that the distortion of the portion of the mesh among the one or more of the portions of the mesh is at or above the threshold of parameterization, an output mesh including the one or more portions of the mesh.

The invention discloses depth-based vehicle environment visualization using generative AI. In various examples, systems and methods related to geometry estimation and dynamic object rendering for vehicle environment visualization are disclosed. The environment around the ego-vehicle may be visualized by extracting one or more depth maps from the image data, converting the depth maps to a 3D surface topology of the surrounding environment, and / or texturing the detected 3D surface topology with the image data. Dynamic objects may be detected and masked from a first pass of texturing. Rigid body dynamic objects may be visualized by warping a respective depth map using a respective trajectory, inserting or fusing the resulting warped 3D representation of each such object into a (textured) 3D surface topology, and texturing the warped 3D representation of each object using a respective image data. The non-rigid dynamic object may be represented as a flat 2D surface and textured with corresponding image data.

The invention discloses an enhanced 3D (three-dimensional) surface reconstruction method based on 3D (three-dimensional) Gaussian Splitting. Global consistent depth priori is obtained through virtual stereo pair rendering; constructing a factor graph and introducing a cross-view geometry / luminosity consistency constraint to form local beam adjustment loss; the prior is used as a learnable parameter to be combined with 3DGS to be optimized, and meanwhile, the Pull loss is assisted to pull low-credibility pixels; and finally, multi-loss function end-to-end training is adopted. The method comprises the following steps of: in Tanksamp; the method has the advantages that F1 is equal to 0.58 and DTU Chamfer is equal to 0.48 mm on a Temples data set, the training time is only 20 min, compared with the prior art, geometric accuracy SOTA and speed magnitude improvement are achieved at the same time, and the method is suitable for VR / AR, robot and industrial measurement scenes.

A Kaleidoscopic Geometric Vision Platform (KGVP) that transforms three-dimensional (3D) machine vision through an optical system that creates multiple virtual laser projectors from a single moving component. A spindle mirror mechanism (SMM) rotates a reflective surface to sweep collimated laser beams in circular patterns. These beams strike a series of kaleidoscopic mirror facets (KMFs) arranged concentrically around the SMM in a concave configuration. Each KMF redirects the rotating beam, creating a virtual projector with a distinct origin point and sweep direction. As the SMM completes one rotation, it generates N distinct laser trajectories (where N equals the number of KMFs), each sweeping from a different virtual origin point. Event-based cameras / sensors positioned strategically around the KMFs detect laser light reflected from object surfaces with microsecond precision. The KGVP triangulates 3D surface coordinates by determining correspondence between detected light and specific virtual projectors based on precise timing information. This approach eliminates the computational complexity typically required for multi-view feature matching, as the KGVP can unambiguously identify which virtual projector created each detected event. With calibration, the KGVP can establish the exact 3D positions of all virtual projector origins and their beam trajectories and build look-up tables that optimize triangulation accuracy. The KGVP enables real-time 3D surface reconstruction with high precision while using far fewer mechanical components than conventional machine vision systems.

In various examples, an environment visualization pipeline may determine whether to generate or otherwise enable a visualization using an environmental modeling pipeline that models an environment as a 3D bowl or using an environmental modeling pipeline that models the environment using some other 3D representation, such as a detected 3D surface topology. The determination may made based on various factors, such as ego-machine state, (e.g., one or more detected features indicative of a designated operational scenario, proximity to a detected object, speed of ego-machine, etc.), estimated image quality of a corresponding environment visualization, and / or other factors. Accordingly, an environment around an ego-machine, such as a vehicle, robot, and / or other type of object, may be visualized in systems such as parking visualization systems, Surround View Systems, and / or others.

The present disclosure relates to the field of medical image processing and, more in particular, to a method for determining an anatomical fracture reconstruction based on one or more medical images of a broken bone, and a system configured for the same. According to an aspect the method comprises the steps of: receiving medical image data associated with the broken bone, identifying the plurality of bone fragments in the medical image data, generating a plurality of 3D surface models that virtually represent the bone fragments; registering a plurality of landmarks matching the surface models; generating a reconstructed model representing a reconstructed form of the broken bone by selecting at least two landmarks; generating a template model representing an optimal alignment of the surface models; repositioning the surface models to align at the selected landmarks set using the template model as reference; iteratively refining the reconstructed model by selecting different landmarks; changing the position of the surface models to align at the different landmarks; evaluating a quality measure that quantifies how changing the position affects the quality of the reconstructed model until a stopping condition is satisfied; and determining an anatomical reconstruction of the broken bone by comparing the position of the identified bone fragments in the medical image data with the position of the corresponding surface models in the reconstructed model.

The invention provides a path texture driven 3D surface processing track generation method and device, and the method comprises the steps: 1, obtaining the coordinates of three vertexes of a triangular patch and a first-order adjacency list of each vertex based on an STL model; step 2, constructing mapping from a curved surface path to a two-dimensional image path based on the vertex coordinates and the first-order adjacency list obtained in the step 1; 3, processing the path texture image to obtain a point sequence, and then reversely mapping the point sequence to the STL model based on mapping to obtain an initial track point set; and step 4, performing optimization processing on the initial track point set to generate a path point set. According to the method, the path texture image and the STL model serve as input, and the continuous track capable of being used for precision machining tasks such as industrial grinding is generated.

This invention provides an automatic calibration method and apparatus for a ship panoramic surround view system based on UAV collaboration and 3D surface mapping. A virtual 3D surface projection model is established in the ship's coordinate system, and the surface normal vectors of sampling points on this model are mapped outwards to generate the UAV's flight trajectory. The UAV, equipped with an RTK positioning module, acts as a dynamic calibration target with precise three-dimensional coordinates as it flies along this trajectory, its spatial distribution naturally matching the geometry of the surface projection model. During flight, images from the UAV are simultaneously acquired by the ship's onboard camera, and pixel coordinates are extracted using a target detection algorithm. Simultaneously, the time synchronization data between the UAV and the ship's onboard RTK module is used to establish the correspondence between pixel coordinates and three-dimensional coordinates in the ship's coordinate system, minimizing reprojection errors and jointly calculating the extrinsic parameters of each camera. This eliminates the dependence on fixed planar references on shore, enabling automated calibration with precise adaptation to the 3D surface projection model in any water area.

An intraoral scanning system (102) includes a handheld intraoral scanner (104), a processor (106), and a continuous volumetric ML model (108) for generating a 3D internal geometry (120) of a tooth (306). The intraoral scanner includes a sensor (214D) for detecting NIR and visible light. The processor receives the visible light and NIR information from the sensor, generates a 3D surface model (118) of the tooth using the visible light information, and determines input parameters of a continuous volume ML model by capturing a 2D NIR image (114) of an interior region of the tooth from the NIR information. Each NIR image contains pixels (722) having a projection object. The input parameters include spatial position and viewing angle, and the projected object contains point coordinates (726, 732). The continuous volume ML model processes the input parameters to determine intensity and density values for pixels in the 3D internal geometry of the 3D surface model.

This invention belongs to the field of contact lens technology, specifically providing a method for designing scleral lenses based on ocular surface and scleral topography. Based on the topography of the anterior surface of the patient's cornea and sclera, the method divides the anterior surface of the cornea and sclera into meridians at equal angles, and designs the surface profile curves of the anterior and posterior surfaces of the scleral lens according to the morphology of the patient's cornea and sclera. Finally, 3D reconstruction is used to obtain the 3D surface profile data of the scleral lens. The optical zone of the scleral lens can be designed in various ways depending on the different shapes of the patient's eyeball; the transition zone can be designed in diverse ways to ensure the thickness of the intraocular fluid at certain locations based on the ocular surface morphology; and the landing zone smoothly conforms to the anterior surface of the sclera. This invention maximizes conformity to the patient's ocular surface morphology, ensures the uniformity of the intraocular fluid, and maintains a high degree of matching with the ocular surface, thereby achieving trial-free scleral lens fitting, improving clinical accuracy and efficiency, and enhancing patient safety and satisfaction.

The present disclosure relates to an intraoral scanning system configured to determine a three-dimensional surface model and a plurality of focus images. The intraoral scanning system comprises: a projector unit configured to emit light onto a dental object, wherein the emitted light comprises an infrared wavelength and a structured light, the structured light comprising a first visible wavelength; a first image sensor unit comprising: a first image sensor configured to acquire first reflected light from the dental object, wherein the first reflected light comprises the infrared wavelength, and wherein the first image sensor comprises a pixel array, a microlens array arranged in front of the pixel array and configured to transmit the first reflected light to the pixel array, wherein one or more microlenses of the microlens array direct the first reflected light to one or more pixels of the pixel array; a second image sensor unit comprising: a second image sensor configured to acquire second reflected light from the dental object, wherein the second reflected light comprises the structured light; a processor unit configured to: determine three-dimensional (3D) data of the dental object based on the second reflected light, determine a three-dimensional (3D) surface model of the dental object by merging the 3D data, and determine a plurality of focus images at different focus depths into the dental object by selecting a set of pixels from the pixel array associated with each microlens of the microlens array, and wherein the processor unit is configured to align a position of each focus image of the plurality of focus images to a position in the 3D surface model based on the 3D data.

A modular, multi-functional, and reusable three-dimensional (“3D”) mounting surface for use in robotic automation to facilitate changing from one robot type to another (e.g., COTS (commercial off the shelf) robot or component) is described. A change involves removing only the surface plates without the entire mounting base plate for each product, which make the manufacture process less costly and faster to deploy. The modular design of the present invention enables a flexible mounting base plate configured to incorporate different types of robot sizes, robot cabinets, and applications. This invention is not only expandable on the three-dimensional (“3D”) tessellated surface for larger robot applications, the 3D surfaces may be combined together to form even larger robot solutions for factory automation. The present invention is reconfigurable with inserts that fit precisely in the mounting base plate.

The invention discloses a non-rigid registration method and device based on 3D surface registration and a storage medium. The method comprises the steps that a 3D image of craniocerebral CT and an intraoperative visible light face image are collected; extracting facial features of the 3D image of the craniocerebral CT by adopting a three-dimensional convolutional neural network, and constructing a CT facial feature point set; extracting facial features of the intraoperative visible light facial image by adopting a three-dimensional convolutional neural network, and constructing a visible light facial feature point set; establishing an initial corresponding relation matrix based on a standard topological structure of the CT facial feature point set and the visible light facial feature point set, and endowing each corresponding relation in the initial corresponding relation matrix with a reliability weight to obtain a face prior corresponding relation; and introducing a face prior corresponding relation as an initial parameter of the t distribution hybrid model, and outputting a registration result after iteratively optimizing the parameter. According to the method, two algorithms are combined for surgical navigation registration, so that a rapid and accurate registration effect is achieved, and the requirements of clinical surgical navigation are better met.

The present disclosure relates to a system and method for improving or refining the accuracy and / or level of detail of a 3D surface based on pixel data from a set of images, such as color data of pixels. In particular, the present disclosure relates to a 3D scanner system comprising an intraoral 3D scanner, comprising: a projector unit comprising a light source and a pattern generating element for structuring light from the light source into a pattern to be projected onto a surface of an object; and two or more cameras configured to acquire a set of images, where the set of images includes images from each camera, where each image includes an array of pixels, each pixel having a pixel color; the scanner system further includes one or more processors operatively connected to the intraoral 3D scanner configured to: generate a three-dimensional (3D) surface of the object based on the set of images obtained from the camera, where the 3D surface includes a plurality of points and / or vertices; and generating a refined 3D surface by solving the optimization problem wherein points and / or vertices in the 3D surface are relocated such that for each point or vertex, a measure based on differences in pixel colors associated with that point or vertex will be minimized.

The present disclosure provides systems and methods for multi-modal analysis of patient-specific anatomical features from medical images. The system can receive a medical image of a patient and metadata associated with the medical image indicative of a selected pathology, and automatically classify the medical image using a segmentation algorithm. The system can use an anatomical feature identification algorithm to identify one or more patient-specific anatomical features within the medical image by exploring an anatomical knowledge dataset. A 3D surface mesh model representing the one or more classified patient-specific anatomical features can be generated, such that information can be extracted from the 3D surface mesh model based on the selected pathology. Physiological information associated with the selected pathology for the 3D surface mesh model can be generated based on the extracted information.

The present technology relates to standardized coordinate systems for mapping three-dimensional structures. An exemplary method includes: obtaining imaging data including a representation of a left atrium of a subject; identifying anatomical features represented in the imaging data, the anatomical features including pulmonary veins that connect to the left atrium; generating a 3D surface mesh corresponding to the left atrium; determining a reference point on the 3D surface mesh based on locations of junctions of the pulmonary veins with the left atrium; establishing a reference axis based on the reference point; determining, on the 3D surface mesh and based on the reference axis, lines of longitude; determining, on the 3D surface mesh, lines of latitude along the lines of longitude; assigning coordinate values to points on the 3D surface mesh based on the lines of longitude and latitude; and generating a 2D map of the left atrium using the coordinate values.

A sensor device for use with a prosthetic socket includes a base material with at least one flexible printed circuit board (PCB) secured to the base material, the PCB having a plurality of pressure sensors. The PCB may include a radial arrangement of multiple PCBs or a single PCB with an integrated sensor array connected to a main processing unit via a flat ribbon cable. Comfort cell sensors with embedded BLE pressure sensors may also be used. The sensor device is positioned between a prosthetic silicone liner and socket to measure interface pressure. The data is processed to generate a real-time 3D pressure heatmap and may also be processed into 3D surface models using backend processing pipelines. Visualization software supports UV mapping, heuristic pressure analysis, and GPU-accelerated rendering, while a mobile application enables real-time interaction with the data for prosthetic fit evaluation.

The utility model relates to a 3D curved surface data acquisition device. The device comprises a first linear motion platform; the supporting seat is arranged on the first linear motion platform in a sliding manner; the rotating platform is rotationally arranged on the supporting seat, a product with a 3D curved surface is arranged on the rotating platform, and the first linear motion platform drives the product to move to a detection position; the motion extension direction of the second linear motion platform is different from that of the first linear motion platform; the sliding support is arranged on the second linear motion platform in a sliding mode, and the laser is obliquely arranged on the sliding support; and the control unit is used for controlling the first linear motion platform, the rotating platform and the second linear motion platform to move, so that the laser obtains 3D curved surface data of the product. According to the utility model, the 3D curved surface product is automatically moved, the curved surface data is comprehensively acquired by laser, and the high-precision detection of the 3D curved surface is assisted.

A system and method for capturing images of a target area includes controlling an image sensor mounted on a gimbal to capture images of the target area over time (S202), and controlling the gimbal to adjust the orientation of the image sensor using an elevator algorithm (S204).

Methods and apparatuses for automating the retopologization of 3D meshes including the automated selection and adjustment of correspondence points are described. The automated selection of correspondence points may be performed to refine locations of correspondence points using a matching score that is computed based on surface normal similarity between surfaces corresponding with a candidate correspondence point on an input scan mesh and a point on a morphable model of 3D surfaces. The matching score may also take into account a distance between a candidate correspondence point on the input scan mesh and a corresponding point on the morphable model of 3D surfaces and similarities in surface features, such as similarities in surface curvature at the candidate correspondence point on the input scan mesh and the corresponding point on the morphable model of 3D surfaces.

A method for deriving a wear state of a soil interaction component of a soil processing implement of a construction vehicle. The method comprises steps of 1.) providing a geometry model regarding an assumed shape of the soil interaction component, 2.) engaging the soil by using the soil interaction component and tracking a motion for deriving tracking data of the soil interaction component, 3.) using the tracking data and the geometry model to derive an expected 3D surface model, 4.) providing visual 3D perception data of a soil area affected by the engaging, such that the visual 3D perception data and the expected 3D surface model can be referenced to one another, and 5.) comparing the visual 3D perception data with the expected 3D surface model and, based thereof, determining a deviation of an effective shape of the soil interaction component from the assumed shape.

In various examples, systems and methods for geometry estimation and dynamic object representation for visualizing the vehicle environment are disclosed. In embodiments, the environment of an ego machine may be visualized by extracting one or more depth maps from image data, converting the depth map(s) into a 3D surface topology of the environment, and / or texturing the detected 3D surface topology with image data. Dynamic objects such as moving vehicles or pedestrians may be detected and masked in a first pass of texturing. Rigid dynamic objects may be visualized by warping corresponding depth values ​​using corresponding trajectories, with the resulting warped 3D representation of each such object being incorporated into the (e.g.,A (textured) 3D surface topology is inserted or merged, and the distorted 3D representation of each object is textured using corresponding image data. Non-rigid dynamic objects can be represented as flat 2D surfaces and textured using corresponding image data.

This invention relates to the field of intelligent inspection and 3D visual reconstruction technology for automotive parts, specifically a method for 3D image reconstruction of lightweight internal high-pressure molded parts for automobiles. The method includes: acquiring a sequence of structured light images, multispectral reflectance texture images, and a priori simulation model of the target object, and completing spatial coordinate registration; dynamically allocating edge extraction weights based on the local curvature gradient of the 2D image to generate a non-uniform density 3D point cloud; constructing a surface reconstruction energy function using surface reflectance variation data as a penalty term, fitting the point cloud to the 3D surface, and generating a target 3D mesh model; fusing 3D geometric features, 2D texture features, and the priori simulation model, and outputting the wall thickness reduction rate and residual stress distribution via a graph neural network; generating and overlaying a risk heat map, and outputting the evaluation decision results. This invention extends from geometric reconstruction to risk semantic reconstruction, improving the comprehensiveness and reliability of online inspection of internal high-pressure molded parts.

A computer-implemented method and apparatus for generating a quadrilateral grid from an image with an alpha channel. The method includes receiving an image with an alpha channel depicting a shape mapped onto a 3D surface, vectorizing the shape to create a vector path, determining corners by calculating a centroid and identifying the points, correcting a winding order to ensure a clockwise orientation, constructing a quadrilateral grid by setting sub-paths based on detected corners, resampling the sub-paths to match specified rows and columns, performing weighted interpolation across the grid using inverse square distance weighting, and outputting the generated quadrilateral grid for display on a computer device. The apparatus comprises a processor configured to execute these steps, including vectorizing the shape, determining corners, correcting the winding order, constructing and resampling the grid, performing weighted interpolation, and subdividing the 3D mesh for flexible manipulation and extrapolation.

Methods and systems are described that generate three-dimensional (3D) measurements from points in two-dimensional (2D) images. An example method includes determining an alignment between a 2D image of a dental site and a 3D surface of the dental site, determining a first point and a second point in the 2D image, projecting the first point and the second point onto the 3D surface based on the alignment between the 2D image and the 3D surface, performing a measurement of a distance between the projected first point and the projected second point on the 3D surface, and displaying at least one of a) a first visualization of the measurement on the 2D image or b) a second visualization of the measurement on the 3D surface.