70 results about "Landmark point" patented technology

The invention relates to the technical field of orthodontics and medical image processing, in particular to an artificial intelligence-based automatic positioning method and system for a maxillary bone expansion device. The positioning method comprises the following steps: taking a cone beam computed tomography image and intraoral scanning data of a patient; segmenting a key anatomical structure based on the scanned image, wherein the key anatomical structure comprises an incisor foramen and a transverse palate slit; automatically identifying a plurality of cranio-maxillofacial mark points based on the scanned image, and establishing a maxilla three-dimensional coordinate system; based on the three-dimensional coordinate system, the intraoral scanning data and the key anatomical structure, positioning adjustment is carried out on the arch expander to determine the final positioning posture, and positioning adjustment comprises the steps that the safe distance between the arch expander and the surface of the palate mucosa is screened, and contact with the key anatomical structure is avoided; and outputting the three-dimensional parameters of the final positioning posture. According to the invention, the automatic, intelligent and safe placement of the arch expanding device is realized, so that the design efficiency is improved, the operation difficulty is reduced, and the clinical safety and the arch expanding effect are guaranteed.

The application provides a method and system for spatial calibration of a radar device. The method comprises: obtaining an image and radar measurement data at the same time, the radar measurement data comprising radar coordinates of a plurality of landmark points in a geographic region; obtaining geographic coordinates of the landmark points recorded in the image according to pixel coordinates of the landmark points recorded in the image; determining at least two landmark point matching pairs, each landmark point matching pair comprising a geographic coordinate of a landmark point and a radar coordinate of the landmark point; and obtaining a calibration relationship between the radar measurement data and the geographic region according to the at least two landmark point matching pairs. The method can improve the accuracy and efficiency of spatial calibration.

The invention discloses a mark point layout method and device for rotation monitoring and a medium. The method comprises the steps of obtaining a curved surface normal vector and a curved surface center point of a curved surface structure to be monitored; acquiring the optimal position of the binocular camera; obtaining a threshold value of a sight angle of the binocular camera according to the eccentricity of the elliptical distortion of the circular mark point; obtaining the relationship between the visibility of points on each position of the curved surface and the rotation angle of the curved surface structure; obtaining the relationship between the elliptical distortion and the rotation angle of the circular mark point; obtaining an image available frame of each point location under the sight line of the current rotation angle; and constructing mark point selection logic to obtain an optimal layout position of the mark points. The positioning method of the binocular camera and the positioning method of the position of the mark point are adopted to optimize the layout of the mark point, the elliptical distortion of the mark point is reduced, the precision of rotation monitoring is improved, the layout of the mark point can be optimized, the measurement blind area is avoided, the number of the mark point is reduced, the time for pasting and removing the mark point in the measurement operation is shortened, and the measurement efficiency is improved.

This application belongs to the field of computer vision and optical measurement technology, specifically disclosing a point cloud stitching method and apparatus based on monocular pose prior marker matching. The method includes: calculating the pose of multiple markers extracted from left and right camera images, determining the normal vector and three-dimensional coordinates of each marker's circular cross-section in its respective camera coordinate system; transforming the three-dimensional coordinates and corresponding normal vectors of each marker in either the left or right camera image to the other camera coordinate system for marker point registration between the left and right camera images; the circular cross-section is a circular cross-section in three-dimensional space with the origin of the camera coordinate system as its vertex, passing through the elliptical curve where the marker is located; and stitching the three-dimensional point cloud of markers based on the marker point registration results of the left and right camera images. This application can significantly improve the accuracy of binocular stereo marker matching and the system's anti-interference capability in complex industrial scenarios.

The application provides a triangular facet data management method, device and XR equipment, relates to the technical field of data processing, and the method comprises the following steps: performing spatial grid division on initial three-dimensional landmark points to construct a grid map; performing surface reconstruction on the three-dimensional landmark points in the grid map to obtain triangular facet data of each grid; obtaining vertex indexes of the triangular facets according to the triangular facet data; and calculating hash indexes of the triangular facets according to the vertex indexes of the triangular facets, so as to map the triangular facets to a triangular facet index list of the corresponding grid. The application can solve the problem that the existing triangular facet data management method is difficult to realize fast and accurate query of triangular facet data.

The application relates to a landmark point matching method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a scanning point cloud obtained by shooting a calibration object under a current scanning visual angle; the calibration object comprises a landmark point; matching the calibration object point cloud with the scanning point cloud to obtain a first matching point pair; the first matching point pair comprises a calibration object matching point and a matching scanning matching point; projecting the scanning matching point to an image coordinate system of a camera to obtain an image mapping point; obtaining a calibration object image obtained by shooting the calibration object by the camera; matching the image mapping point with the landmark point on the calibration object image to obtain a second matching point pair; the second matching point pair comprises a scanning matching point and a matching landmark point on the calibration object image; for the camera, determining a target matching point pair of the landmark point on the calibration object image and the landmark point on the calibration object based on the first matching point pair and the second matching point pair. The method can obtain more accurate target landmark point pairs and optimize unstable factors of the equipment.

Systems and methods of landmark detection using deep neural networks with multi-frequency self-attention are provided. The system includes an encoder network that receives an image of an object of interest as an input and generates a multi-frequency feature map as an output. The system also includes an attention layer that receives the generated multi-frequency feature map and refines the generated multi-frequency feature map based on a correlation or association between the received multi-frequency feature maps. The system further includes a decoder network that receives the refined multi-frequency feature map from the attention layer as a second input and generates a landmark detection result based on the second input. The landmark detection result includes a heat map image of the object of interest, and the heat map image indicates locations of landmark points on the object of interest in the image.

A method of generating a correction plan for correcting a deformed bone includes inputting to a computer system a first image of the deformed bone in a first plane and inputting to the computer system a second image of the deformed bone in a second plane. Image processing techniques are employed to identify a plurality of anatomical landmarks of the deformed bone in the first image. The first image of the deformed bone is displayed on a display device. A graphical of the deformed bone is autonomously generated and graphically overlaid on the first image of the deformed bone on the display device, the graphical template including a plurality of lines, each line connected at each end to a landmark point corresponding to one of the anatomical landmarks. A model of the deformed bone may be autonomously generated based on the graphical template.

The invention relates to an SLAM back-end optimization method based on sparse matrix factorization and a hardware accelerator architecture, and the method comprises the steps: constructing a Hessian matrix through employing a binary sparse coding mechanism according to the actual observation coordinates of feature points on an image plane and the predicted coordinates of road sign points projected to a camera coordinate system; performing Schel elimination processing on the Hessian matrix based on binary sparse coding to obtain a linear equation set only containing a camera pose variable; and carrying out extended Kalman filtering on a linear equation set only containing a camera pose variable to realize incremental updating of a state pose and a road sign point coordinate. According to the method, the overall delay of SLAM rear-end optimization can be remarkably reduced, and the real-time requirement in a high-speed moving scene is met.

The invention requests to protect an unsupervised anatomical mark point accurate positioning method based on double-layer alignment and a super-resolution head, and aims to solve the problem of domain migration caused by differences of different clinical center imaging devices. Comprising the following main steps: S1, constructing an input layer alignment module, generating a target style image by adopting adaptive instance normalization, and meanwhile, retaining an original spatial anatomical structure; s2, constructing an output layer alignment module, adopting a mean value teacher framework, and guiding student model learning through a high-quality pseudo tag and a self-adaptive mark point shielding strategy; and S3, introducing a lightweight super-resolution head, fusing the multi-scale features extracted by the backbone network, and generating a high-resolution heat map by adopting pixel rearrangement. Compared with an existing method, the method has the following advantages that (1) the cross-domain adaptive capacity is effectively improved through input-output double-layer alignment; (2) the super-resolution head can directly decode the coordinates without tedious post-processing, so that the quantization error and the calculation complexity are reduced;

A muscle movement information-containing intraoral scanning data accurate acquisition method comprises the following steps: S1, collecting a single-frame texture map including an intraoral photo or a dental scanning image, marking an attached gum boundary by using a dental professional, creating a ground truth segmentation map, and performing creation and training of an attached gum area automatic segmentation model after performing variant on U-Net; s2, generating edge line data by utilizing Poi ntNet + + based on gypsum model scanning and artificially described edge lines, and creating and training an automatic edge line generation model; the model aims at automatically generating accurate edge lines for the intraoral scanning data obtained in the step S4 and guiding manufacturing of the movable restoration; s3, dynamically recording three-dimensional form information of intraoral muscles of the user in a motion state; s4, the obtained dynamic data and conventional static oral scanning data are guided by mark points to be elastically registered, and an intraoral data sequence with the complete form is obtained.According to the method, the implementation scheme that oral scanning is used for replacing impression taking can be achieved.

This application relates to a marker point matching method, splicing method, apparatus, device, and storage medium. The method includes: obtaining a current frame marker point set and a buffer frame marker point set; the current frame marker point set includes current frame marker points; the buffer frame marker points in the buffer frame marker point set are selected from global marker points; obtaining a first distance matrix corresponding to the current frame marker points and a second distance matrix corresponding to the buffer frame marker points; based on the first and second distance matrices, obtaining a pair of matching points with the same name for the current frame marker points and the buffer frame marker points; the matching point pair includes the same-name points of the current frame marker points; updating the buffer frame marker points based on the same-name points of the current frame marker points to obtain updated buffer frame marker points; the updated buffer frame marker points are used for matching with marker points in the next frame. This method can shorten the marker point matching time, thereby improving real-time performance.

The application provides a digital oral model mark point recognition method and device and electronic equipment, and the method comprises the following steps: step 1, inputting dental arch model image data, segmenting the dental crown of the dental arch model, and recognizing the tooth position number of the dental crown, wherein the dental arch model comprises a gum and dental crowns of different tooth positions. Step 2, based on automatic recognition of the dental crown mark point of a single dental crown, for each segmented dental crown, the multi-view graph network is used to automatically recognize the dental model mark point, and the mark point on each dental crown is obtained. The method of the application does not predict the mark point on the three-dimensional point cloud, but maps the three-dimensional data into two-dimensional projection image data, and calculates by using a two-dimensional network, so that the calculation amount and the dependence on the computing power can be reduced compared with a three-dimensional network.

The method includes accessing a plurality of reference landmark points associated with a plurality of features in a reference image, accessing a reference measurement point corresponding to an asset in the reference image, receiving a target image including the features and the asset, identifying a plurality of target landmark points of the target image corresponding to the features, generating a mapping from the reference landmark points to the target landmark points, determining, using the mapping, a target measurement point corresponding to the asset in the target image, and extracting, from the target measurement point of the target image, a temperature measurement of the asset.

The invention relates to the technical field of image positioning, and discloses a 3DGS visual repositioning method and system based on intrinsic image decomposition, a terminal and a storage medium, and the method comprises the steps: obtaining multi-view scene image data, inputting the multi-view scene image data into a three-dimensional Gaussian sputtering model for training, and obtaining an intrinsic 3DGS map model; obtaining a query image to be positioned and a landmark point set, inputting the query image into the internal 3DGS map model for decomposition to obtain a target albedo map, and performing feature matching according to the target albedo and the landmark point set to obtain an initial pose; and rendering the initial pose based on an internal 3DGS map model to obtain a dense candidate albedo map and a depth map, and adjusting the initial pose according to the dense candidate albedo map, the depth map and the target albedo map to obtain a positioning camera pose. According to the invention, visual repositioning is carried out on the query image through the internal 3DGS map model, and accurate visual positioning is realized.

The invention belongs to the technical field of three-dimensional measurement, and particularly discloses a high-robustness mark point matching method and device, and the method comprises the steps: obtaining a distance matrix under adjacent visual angles based on a mark point set S and a mark point set T under the adjacent visual angles; searching potential matching point pairs between S and T based on a preset screening condition and the distance matrix under the adjacent view angles; respectively screening X mark points closest to the center of the mark point from S and T, and putting the X mark points into two candidate point sets; based on a preset screening condition and the distance matrixes corresponding to the two candidate point sets, candidate point pairs between the two candidate point sets are searched, and a pair of reference points is screened out from the searched candidate point pairs; and based on the found potential matching point pair and the found pair of reference points, through matching point pair search based on congruent triangles, screening out two pairs of reference points from the found potential matching point pair. According to the invention, the robustness of three-dimensional data splicing can be effectively improved.

The application discloses a positioning method of human joint anatomical landmark points, and comprises the following steps: collecting human DICOM image data sets of different objects, reconstructing sequence files in the DICOM image data sets to generate three-dimensional CT images; generating two-dimensional DRR images in the orthosteric direction of the three-dimensional CT images, constructing joint regions and anatomical landmark point identification models of the two-dimensional DRR images, and identifying the positions of the anatomical landmark points on the orthosteric DRR images; generating axial tomographic images on the three-dimensional CT images according to the coordinate information of the landmark points on the orthosteric DRR images, constructing joint regions and anatomical landmark point identification models of the two-dimensional axial tomographic images, and identifying the positions of the anatomical landmark points on the axial tomographic images again; positioning the positions of the anatomical landmark points through the outputs of the two models, and obtaining complete three-dimensional coordinates of the joint anatomical landmark points. The application improves the accuracy of joint anatomical landmark point identification and has high identification efficiency.

A system and method for hierarchical spectral landmark graphs in cognitive manifolds implements cognition through discrete landmark structures that provide scalability, interpretability, and auditability. The system maintains a landmark graph on a cognitive manifold with vertices representing landmark points selected based on geometric properties including curvature and cognitive trajectory density. A spectral basis derived from the landmark graph encodes long-term semantic structure. Spectral continuation updates the basis when geometric invariants indicate structural change, while enforcing differential plasticity constraints protecting foundational low-frequency modes. Reversible edges constructed with forward and reverse displacement vectors enable auditable trajectory replay through cryptographic certificates and manifold journals. The system generates probability estimates by fusing geometric priors from landmark paths, empirical evidence from simulations, and historical evidence from archived cases. Landmark-conditioned naturalization produces interpretable explanations mapping geometric structures to domain-specific semantic labels, enabling transparent, auditable reasoning grounded in verifiable landmark-based evidence.

Embodiments of the present application provide a three-dimensional reconstruction method, device, equipment and storage medium. A landmark point can be set on a surface of a target object, and a structured light is projected to the surface of the target object in at least a part of a time period during which the target object is scanned, so as to collect a set of image frames of the target object. Then, a three-dimensional point cloud of landmark points of each frame is reconstructed based on each image frame containing a landmark point pattern, and a three-dimensional point cloud of the target object of each frame is reconstructed based on each image frame containing a structured light pattern. Since a coordinate conversion relationship between the three-dimensional point clouds of the landmark points of each frame can be accurately determined, and a coordinate conversion relationship between the three-dimensional point cloud of a single frame of landmark points and the three-dimensional point cloud of a single frame of the target object can also be determined, the landmark points can be used to assist the splicing of the three-dimensional point clouds of the multiple frames of the target object, so as to obtain a more accurate splicing result.

This invention relates to the technical field of breast ultrasound image recognition, specifically to a method and system for detecting abnormalities at ultrasound puncture sites based on image processing. In a patient's breast ultrasound image, all similar pixels of a reference pixel are acquired. A spatial coherence coefficient is calculated based on the distance distribution between the reference point and each similar pixel, the number of similar pixels, and regional distribution characteristics. Hyperechoic regions are identified by combining pixel grayscale distribution. For each hyperechoic region, landmark and non-landmark inflection points are detected. An abnormal extension coefficient is calculated based on the positional distribution of landmark and non-landmark points; thus, an abnormality factor is obtained, and abnormal inflection points are screened. Abnormal inflection points are clustered based on the abnormal extension coefficient and abnormality factor to form abnormal clusters. Contour fitting is performed on the abnormal inflection points within each cluster to obtain suspected mass regions. This invention can accurately identify suspected mass regions, thereby improving the detection efficiency and accuracy for relevant personnel.

The application provides a real-time acupoint tracking method and system and a guasha robot, and relates to the technical field of computer vision recognition. The tracking method comprises a static positioning stage, a two-stage training strategy for fusing traditional Chinese medicine meridian prior knowledge is used to improve the YOLO-Pose model, bone landmark point detection accuracy is improved through meridian perception approximate training and adaptive fine adjustment, and a standardized coordinate system is established based on the bone degree and inch method to realize accurate acupoint mapping; in the dynamic tracking stage, a two-stage optimization complementary filter is used to smooth the acupoint coordinates in the video sequence, and high-frequency jitter is inhibited through a speed smoothing mechanism and historical trajectory weighted fusion. The application solves the problems of traditional guasha relying on experience and large dynamic tracking jitter, improves image detection accuracy, optimizes the balance relationship between smoothness, response speed and accuracy of the dynamic trajectory generated by the image, and realizes high-precision and high-real-time acupoint positioning and tracking.

The application provides a large rotary equipment blade measurement system calibration method based on a topological structure landmark point coding, and belongs to the field of blade appearance three-dimensional measurement. Firstly, the three-dimensional landmark points are projected onto a two-dimensional plane by using a principal component analysis method. Then, a local geometric descriptor is generated for each point on the projection plane. The cross-frame matching and trajectory tracking of the landmark points are realized through the descriptor matching. Finally, the center point and normal vector of all trajectories are extracted, the average value of the center point coordinates and the average value of the normal vector are calculated, and the rotary shaft axis linear solution is taken as the rotary shaft pose calibration. The application takes a disc with circular landmark points as a calibration module, designs a position tracking descriptor based on the topological relationship between the landmark points in the disc plane, realizes the landmark point position tracking, has important significance for the rotary shaft pose calibration, and provides a strong technical foundation for the subsequent blade splicing measurement based on the axis calibration.

The application relates to a SLAM method fusing dynamic landmark information constraints in a dynamic environment and belongs to the field of automatic driving. The method comprises the following steps: using a deep learning network, a multi-view geometry method, an optical flow, a scene flow and the like to realize the differentiation of image points corresponding to dynamic and static landmark points in images; a judgment mechanism for whether to use dynamic landmark points to fuse residual error equations for camera pose solving is proposed; a novel management strategy for dynamic landmarks in a dynamic scene is proposed; when the condition for using dynamic landmark points is met, the motion information of the dynamic landmark is added to the residual error equation as auxiliary priori; when the condition for using dynamic landmark points is not met, it is indicated that the current scene is sufficient to meet stable camera pose estimation, the pose of the dynamic landmark is solved, and motion target tracking perception is realized. The application enhances the robustness of the system in a high dynamic environment and realizes real-time positioning and perception of a local dynamic environment.

According to one aspect of the disclosure, a computer-implemented method of dynamic head generation is provided. The method can include computing a linear blend skinning (LBS) binding system associated with a virtual avatar head based on a set of mesh deformations for a plurality of poses of the virtual avatar head. The LBS binding system can include a set of skin joints and a set of joint weights. Each joint weight of the set of joint weights can be assigned to a vertex of a mesh of the virtual avatar head in a neutral pose. The method can include computing an adjusted head control cage of the virtual avatar head based on a correspondence between the mesh of the virtual avatar head in the neutral pose and a template head control cage using a landmark point prediction model or a regression model. The method can include animating the virtual avatar head based on the LBS binding system and the adjusted head control cage.

A system and method for adaptive geometric diffusion projection enables mapping of heterogeneous high-dimensional representations onto a shared low-dimensional manifold without neural network training. The system maintains landmark points in source spaces and computes their spectral coordinates through graph Laplacian eigen decomposition based on semantic similarities. New input points are projected via harmonic extension, computing weighted interpolations of nearby landmark spectral coordinates. A geometric optimization process refines positions while maintaining manifold constraints through tangent space projections. The system continuously monitors geometric invariants including principal angles, spectral gaps, and curvature distributions. When invariants exceed thresholds, targeted adaptations occur: spectral basis updates using warm-started iterations, landmark set augmentation in high-residual regions, or parameter adjustments. The approach supports logarithmic computational scaling, enables streaming operation on continuous data, and handles multimodal inputs through reliability-weighted consensus. The system maintains projection quality indefinitely through continuous geometric monitoring and local adaptations.

A method for a re-localization of a HMD device may comprise obtaining feature points of objects identified in their current position. The method may comprise obtaining landmark points associated with each of the identified objects from the feature points corresponding to pre-stored landmark points associated with each of the identified objects. The method may comprise determining whether any objects have moved to the current position from a pre-stored position by comparing the obtained landmark points with the pre-stored landmark points associated with each of the objects. The method may comprise filtering the landmark points by discarding the feature points associated with the objects that have moved to the current position from the pre-stored position. The method may comprise performing re-localization of the HMD device using the filtered landmark points.

The application relates to the technical field of intelligent detection, in particular to an edge fatigue detection method and device based on adaptive threshold adjustment and a medium. The method comprises the following steps: acquiring facial image data and facial infrared data of a real-time state of a driver; pre-processing the facial image data and the facial infrared data; positioning facial landmark points of the pre-processed facial image data and facial infrared data through a facial feature detection model to obtain an enhanced 3D landmark point image; comparing the enhanced 3D landmark point image with a physiological feature database to obtain physiological data; and calculating the physiological data through a dynamic threshold decision model and a multi-index fusion engine to obtain a fatigue decision. The method can improve environmental adaptability, realize individualized accurate adaptation, accurately adapt to individual differences and enhance multi-working-condition robustness.

This application relates to the field of intelligent autonomous unmanned systems technology, and particularly to a path planning method and apparatus for intelligent unmanned systems based on a grid bridge detection method. The method includes: modeling the entire environment as a grid map based on the size of the intelligent unmanned system and the maximum width of the current channel; using orthogonal bridges to determine the grids within the current channel and storing them in a list; extracting channel boundary points that meet preset judgment criteria to construct a connected landmark map; generating a path connecting the starting point and the target point; and obtaining the final planned path for the intelligent unmanned system. This application's embodiment can perform grid point detection for the current channel based on initial environment modeling and extract current channel boundary points to construct a connected landmark map, ultimately generating the intelligent unmanned system path. By rapidly identifying landmark points within the current channel, the construction rate of the connected landmark map is improved, thereby enhancing the efficiency and accuracy of intelligent unmanned system path planning.

The application provides a method and device for determining jaw facial symmetry based on a three-dimensional image. The method comprises the following steps: in response to a request instruction input by a user, acquiring a three-dimensional image of the jaw face of the user and complaint information input by the user; identifying position information of a plurality of preset landmark points in an image region; determining second scoring information of the image region according to the position information of the preset landmark points; if the request instruction indicates that the user currently does not need expert evaluation services, determining asymmetry result information of a part corresponding to the image region according to the complaint information and the second scoring information; and pushing the asymmetry result information to the user. The application divides the three-dimensional image of the jaw face into image regions, so as to obtain asymmetry result information of each image region in the jaw face, and makes the asymmetry result more comprehensive. Furthermore, the asymmetry result can be determined in combination with the information and the second scoring information, so as to improve the accuracy of the asymmetry result evaluation.