200 results about "Head model" patented technology

The invention discloses a brain power supply imaging method and system based on a physical information neural network. The method comprises the following steps: establishing a three-layer boundary element method head model based on a Maxwell equation set under quasi-static approximation and calculating a lead matrix; carrying out filtering, artifact suppression and standardization processing on the multi-channel electroencephalogram signals; inputting the standardized signal into a neural network encoder to extract a time sequence feature tensor, estimating the source current density based on the feature tensor, and performing forward calculation by using the lead matrix to obtain a predicted scalp potential; constructing a mixed loss function consisting of a data fidelity item, a physical consistency item and a physical heuristic regularization item, and performing network training and optimization by taking minimization of the loss function as a target; and when the training meets a convergence condition, outputting a visualization result of the brain endogenous current density spatial distribution. According to the method, electromagnetic physical constraints are introduced, so that the physical consistency, interpretability and stability of electroencephalogram inversion are improved.

The invention discloses an epilepsy region positioning method and system based on brain power supply imaging and a dynamic brain network, and the method comprises the steps: obtaining T1 weighted magnetic resonance imaging data of a user, and constructing an individual three-dimensional head model through a boundary element method; acquiring scalp electroencephalogram data of a user, and preprocessing the scalp electroencephalogram data; based on an individual three-dimensional head model, performing inverse problem solving on the preprocessed scalp electroencephalogram data by using a standardized low-resolution brain power source imaging algorithm to obtain source current density signals of 68 brain regions; decomposing into six frequency bands, calculating the power spectrum density of each brain region and carrying out normalization processing, and screening effective frequency bands; based on the source current density signals of the 68 brain regions of the effective frequency band, information flow directions and intensities of different brain regions are calculated by adopting a directional transfer function method, a directional transfer function matrix of the effective frequency band is formed, and a directed brain network is constructed; and calculating a graph theory index and / or an epilepsy index of each brain region, carrying out maximum value normalization analysis, and determining an epilepsy region positioning result.

The invention discloses a method, device and equipment for generating a head model, a storage medium and a program product. The method is characterized by comprising the following steps of: receiving and verifying original three-dimensional T1 weighted image data and an original three-dimensional grid model; performing tissue segmentation based on the verified three-dimensional T1 weighted image data and the original three-dimensional T1 weighted image data to obtain a cerebral grey matter mask, a cerebral white matter mask, a scalp mask and a skull mask; performing topological structure repair on the brain grey matter mask and the brain white matter mask to obtain a brain mask; respectively converting the scalp mask, the skull mask and the brain mask into a scalp mesh model, a skull mesh model and a brain mesh model; calculating and applying a spatial transformation matrix from the verified three-dimensional grid model to the scalp grid model, and performing spatial registration and fusion on the scalp grid model, the skull grid model and the brain grid model to obtain a head model; the method has the advantages that the efficiency, precision and robustness of head model generation are effectively improved, and the method has good cross-platform deployment capability.

The invention discloses a three-dimensional head model generation method based on Gaussian point cloud reconstruction of forward propagation, and the method comprises the steps: compressing an input image to a potential space, obtaining a potential state, and extracting the identity information of the input image at the same time in a stage of generating a multi-view image; de-noising is carried out through a de-noising U-Net with a space and time attention module, and a multi-view image is generated through a VAE decoder and is used for training a weight fine tuning network; in the Gaussian reconstruction stage, the world coordinate origin and the light direction of the camera where each pixel in the multi-view images generated by the video diffusion model is located are calculated, the multi-view images are spliced in the channel dimension through the corresponding light embedding and light direction obtained through calculation, network input features are formed, and the network input features are used as network input features. An asymmetric Gaussian generation UNet based on LGM network improvement is utilized, a feature map is generated according to a multi-view image generated by a video diffusion model, and channel flattening processing is performed on the feature map to obtain a Gaussian point cloud. According to the invention, a more vivid and lifelike 3D head model with high quality can be generated.

The invention relates to a heterogeneous human head model construction method and system oriented to multi-physics field simulation, based on real human head T1 weighted magnetic resonance image data, key tissues such as white matter, gray matter and cerebrospinal fluid are accurately segmented, and a three-dimensional geometric model used for generating carrying tissue identification information is researched and developed; converting the model data into a file format conforming to the NASTRAN standard by utilizing an independently developed format conversion program, and completely retaining organization classification information; finally, different tissue areas are automatically recognized through physical field simulation software, corresponding frequency dependent material attributes are distributed, and a finite element model capable of being directly used for simulation is formed. According to the method, seamless integration of the high-precision heterogeneous human head model and the simulation platform is achieved, tedious manual repairing and assignment operation is not needed, the method has the advantages of being high in precision, high in efficiency and good in compatibility, and the authenticity and reliability of biomedical simulation such as transcranial magnetic stimulation and radio frequency coil design can be remarkably improved.

The invention discloses a fitting uniformity detection method and device, electronic equipment and a storage medium, and relates to the technical field of head-mounted display device.The method comprises the steps that in a first time interval when to-be-detected equipment is installed on a head model, a driving assembly is controlled to drive the head model to swing in a preset first driving mode; within a second time interval when the to-be-tested equipment is installed on the head model, the driving assembly is controlled to drive the head model to swing in a preset second driving mode, and the swing amplitude of the head model in the second driving mode is larger than that in the first driving mode; collecting a first pressure data graph in a first time interval through a pressure sensor, and collecting a second pressure data graph in a second time interval; and according to the first pressure data graph and the second pressure data graph, determining a fitting uniformity result of the to-be-tested equipment. According to the invention, the accuracy of fitting uniformity detection of the head-mounted display device can be improved.

A model processing method includes, obtaining a first source head model and a plurality of pieces of expression feature data; performing deformation matching on the first source head model according to a first model feature of a target head model, to obtain a second source head model; determining a deformation parameter according to a first deformation relationship between the first and second source head models and a second deformation relationship from a first model expression to a second model expression, the first model expression being determined according to neutral feature data of the first source head model, and the second model expression being determined according to expression feature data indicated by an expression movement instruction in the plurality of pieces of expression feature data; and performing expression transfer on the target head model according to the deformation parameter, to obtain a target head model having the second model expression.

The utility model provides a testing device and a testing system. The testing device comprises a track structure; the rotating structure comprises a base slidably connected with the track structure and a rotating assembly capable of rotating relative to the base, a supporting rod is fixedly connected to the center of the rotating assembly, and a rotating shaft assembly is rotatably connected to the top end of the supporting rod; the human body model sleeves the periphery of the supporting rod and can rotate relative to the base around a first rotating center along with the rotating assembly; the head model is fixedly connected with the rotating shaft assembly and can rotate relative to the supporting rod around the second rotating center along with the rotating shaft assembly; an image acquisition and recognition part is arranged on the rotating shaft assembly to recognize an image in front of the human body model and judge a test result. The testing device and the testing system can effectively and accurately complete testing distance changing, head turning and nodding actions so as to meet the testing requirements, are higher in accuracy, can automatically judge the testing result, greatly improve the testing efficiency and liberate manpower.

The utility model relates to a device for measuring an effective protection area of an eye protector, and the device comprises a head model which is used for the wearing of the eye protector and the evaluation of the effective protection area, and comprises a protection area mark; the spraying device comprises a nozzle, a pressure adjusting device and a solution containing cavity, the nozzle is used for spraying a solution, and the diameter of the nozzle is adjustable so that the distribution state of the solution on the eye protector can be changed; the pressure adjusting device is used for adjusting the injection pressure of the solution; and the solution accommodating cavity is used for accommodating a solution. By arranging the head mold and the eye protector marked with different protection areas, the effective protection area of the eye protector can be measured. By arranging the nozzle with the adjustable diameter, the distribution state of the solution on the eye protector or the head mold is changed, so that the measuring device can simulate various biological hazard scenes. The pressure adjusting device is combined with the nozzle for use, the actual spraying scene can be better fitted, and the effective protection area of the eye protector is further accurately measured.

The invention relates to the field of computer vision, in particular to a hair model generation method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining a head shape base of a standard head model; obtaining a standard hair model; acquiring a hair shape base of the standard hair model according to the head shape base and the standard hair model; a shape coefficient of a target head model is obtained, the shape coefficient is obtained according to a target face image, and the target head model is obtained according to the standard head model, the head shape base and the shape coefficient; and obtaining a corresponding target hair model according to the hair shape base and the shape coefficient. The method can be used for generating the hair model with high quality, high matching degree and high flexibility, and the generation efficiency of the hair model is improved.

The invention relates to the technical field of artificial intelligence, in particular to a cross-domain self-adaptive target detection method based on data deviation and training deviation, and the method comprises the steps: constructing a depolarization double-detection-head model based on a Clean detector and a Pseudo detector; performing optimization processing on the debiased double-detection-head model based on a class embedding guided cross-domain true value instance alignment algorithm to obtain an optimized debiased double-detection-head model; and constructing an overall loss function of the optimized depolarization double-detection-head model to obtain a complete depolarization double-detection-head model. Source domain labeling data and target domain pseudo label data are processed in a task decoupling mode, and the stability and generalization ability of cross-domain target detection are improved; a trainable category embedding vector is introduced, so that the detection capability of the model on rare categories is enhanced; a multi-loss collaborative cross-domain optimization objective function is constructed, the learning ability of the model for domain invariant features is enhanced, and theoretical and practical support is provided for a detection task in a complex cross-domain scene.

1. The name of the design product: swimming cap (5). 2. The use of the design product: for wearing when swimming. 3. The design points of the design product: the combination of shape and pattern. 4. The picture or photo that best shows the design points: perspective view. 5. The head model in the design picture is a background and does not belong to the content of the claimed design.

The application discloses a human head dynamic modeling relightable Gaussian mixed shape method, which comprises training image collection and preprocessing, mesh mixed shape training, Gaussian mixed shape training and human head animation generation. The relightable Gaussian mixed shape expression comprises a mesh mixed shape and a Gaussian mixed shape; the mesh mixed shape is used for capturing individual characteristics and is responsible for normal and visibility calculation; the Gaussian mixed shape is responsible for coloring and final image rendering; both are composed of a neutral model representing a neutral expression and a plurality of base expression models corresponding to basic expressions. Human face and head models of arbitrary expressions are efficiently generated by linearly mixing the neutral model and the base expression models. The application expands the Gaussian mixed shape expression without reducing drawing quality and running speed, so that the Gaussian mixed shape expression supports relighting applications, and better serves the production of applications such as movies, animation production, network games and remote conferences.

To provide a three-dimensional head model generation system, program and three-dimensional head model generation method capable of generating an accurate three-dimensional model even when generating a three-dimensional model of a head of an object person who is difficult to keep a stationary state.SOLUTION: A three-dimensional head model generation system 1 comprises: an electronic terminal 2 including an imaging unit 21 for capturing an image of a head 41 and a processing unit 20 for processing the captured image of the head 41; and a server 3, where the processing unit 20 of the electronic terminal 2 includes a terminal-side image acquisition unit 201 that acquires a plurality of images of the head 41 captured from different directions by the imaging unit 21, and a filtering processing unit 205 that determines whether or not the images acquired by the terminal-side image acquisition unit 201 are suitable images satisfying prescribed conditions, and where the server 3 includes a three-dimensional model generation unit 303 that generates a three-dimensional model representing a three-dimensional external shape of the head 41 on the basis of the plurality of suitable images.SELECTED DRAWING: Figure 6

The invention discloses a geological double-dessert prediction method and device based on knowledge graph representation learning, equipment, a medium and a product, and relates to the technical field of oil and gas exploration and development. The method comprises the following steps: determining a geological knowledge map according to multi-source heterogeneous geological data and a mode layer definition scheme; determining predicted result data according to the geological knowledge map by adopting a double-dessert prediction model; the double-dessert prediction model adopts a double-prediction-head model sharing a bottom-layer GAT encoder; the GAT encoder adopts a graph attention network, the graph attention network comprises a plurality of stacked graph attention layers, and each graph attention layer aggregates node information of neighbor entity nodes through an attention mechanism to perform node feature updating so as to quantify the interaction intensity between the entity nodes. According to the method, geological double-dessert prediction can be realized, and an accurate and reliable basis is provided for efficient exploration and development of oil and gas reservoirs.

The invention discloses a three-dimensional head dynamic reconstruction method based on a single view, and belongs to the field of computer vision. Constructing a multi-view face image data set; taking the left view, the front view and the right view of the same identity as input, and obtaining three-dimensional parameter representation of an initial static head through a pre-trained face parameter regression network; entering a dynamic reconstruction stage of single view input; projecting the Gaussian point cloud to an image plane of a single image through projection transformation, and performing feature extraction on the single image through a convolutional neural network; and carrying out pixel-by-pixel loss calculation on the rendered image and the real image, and optimizing the face parameter regression network. According to the method, a high-quality three-dimensional head model can be reconstructed through single-view input, a realistic head image at any view angle can be efficiently rendered, and the method has the advantages of being high in expression ability, high in rendering efficiency, capable of supporting dynamic updating and good in generalization.

The application relates to a special device and method for detecting the magnetic field and temperature of a transcranial magnetic stimulation therapeutic instrument, wherein the special device comprises a bionic head model, a special support, a magnetic field measuring probe, a temperature measuring module, a device host, a control computer and a data line; the bionic head model is arranged at the bottom of the special support, the magnetic field measuring probe is arranged at the top of the special support, and the device host is connected with the magnetic field measuring probe, the temperature measuring module and the control computer through the data line. The method is characterized in that a bionic head model equivalent to the electromagnetic characteristics of the head is designed, the magnetic field in the space where the model is located and the temperature on the surface of the coil are measured, the magnetic field measurement results are calculated and analyzed, and the measurement results of the maximum magnetic induction intensity, the spatial magnetic field distribution, the output frequency, the stimulation pulse width and the coil surface temperature are obtained. The method is suitable for detecting and calibrating the core parameters in the research and development and clinical use of the transcranial magnetic stimulation therapeutic instrument, and ensures the safety and effectiveness of the transcranial magnetic stimulation therapeutic instrument.

The application provides a three-dimensional image pronunciation process head action simulation method, and belongs to the technical field of three-dimensional virtual images. The three-dimensional image pronunciation process head action simulation method obtains a human face video and corresponding audio from a video library, aligns video frames and audio frames, extracts multiple frames of human face images, head posture parameters and mel spectra as training samples; pre-processes the human face images to generate face images after erasing the mouth; establishes a three-dimensional image head model and trains the three-dimensional image head model by using the training samples. The three-dimensional image head model comprises an audio feature extraction module, a lip shape synchronization module, a mouth generation module, a head posture module and a fusion module. The trained three-dimensional image head model is used to generate a three-dimensional image head model for specific audio. The method greatly reduces the calculation amount, simultaneously enables good linkage between the head posture and pronunciation, and avoids the stiff phenomenon of the three-dimensional image pronunciation process.

The utility model provides a head die for a near-infrared light treatment object, the head die is configured to be used for measuring light attenuation and transmission conditions in an accommodating space of near-infrared light treatment equipment, the absorption rate of the surface of the head die for near-infrared light is greater than a preset absorption rate, the structure meets a first group of structure parameters, and the first group of structure parameters comprises: the head circumference is 525-583 mm, and the head circumference is greater than the preset absorption rate. The length of the head ranges from 170 mm to 196 mm, and the width of the head ranges from 140 mm to 166 mm. On the basis of the corresponding condition of the head model and the real human body, as for the performance shown by the near-infrared light treatment equipment designed by using the head model, it can be considered that the near-infrared light treatment equipment can show the same performance on the real human body, and therefore the near-infrared light treatment equipment can be improved in a targeted mode. Therefore, the head die can be used for detecting and improving near-infrared light treatment equipment for performing near-infrared irradiation on the head.

The embodiment of the invention discloses pressure measuring equipment and a manufacturing method of the pressure measuring equipment, the pressure measuring equipment comprises a head model, a circuit layer and a sensing layer, the head model is provided with a plurality of detection areas, and the plurality of detection areas are electrically connected; the circuit layer is directly arranged in the detection area through a laser direct forming process, and the circuit layer is of a multi-point matrix type electrode structure; the sensing layer is located on the outer side of the detection area and covers the circuit layer, and the sensing layer is electrically connected with an electrode of the circuit layer and forms a pressure detection area. Therefore, irregular surface characteristics of a human head model can be adapted, tight attachment of the circuit layer and the detection area is ensured, measurement errors caused by poor contact are reduced, and the pressure measurement precision can be improved.

The application provides a vertical shaft cutting head efficient design method and system, belongs to the technical field of underground coal mine transportation equipment, and comprises a modeling simulation module, a data processing module and an auxiliary module. The modeling simulation module generates a parameterized cutting head model according to input parameters and performs grid division, configures boundary conditions and control parameters required for simulation and performs fluid-solid coupling simulation; the data processing module automatically extracts a slagging index in a simulation result, and completes slagging performance analysis of the parameterized cutting head model; the auxiliary module establishes a working condition-performance-scheme template database, and selects a scheme template according to actual working condition requirements, and assists in realizing scheme integration and local fine adjustment of the scheme, and improves design efficiency. The application realizes whole-process automation and modular design, significantly reduces manual workload, and solves technical problems such as low modeling efficiency, repeated parameter setting and complicated data processing in existing cutting head design.

The utility model relates to an ophthalmology multi-position skill training simulation teaching aid, which belongs to the field of simulation teaching aids and comprises a support, a head model, a neck model, a replaceable eyeball model and a fixed eyeball model. Threaded holes A are respectively formed in two sides of the neck model; the bracket comprises a base, a height adjusting rod, a connecting block and a head model clamping component; the head model clamping and fixing assembly comprises two clamping and fixing plates and two screw rods; the height adjusting rod is connected between the base and the connecting block; the two clamping plates are L-shaped, vertical rods of the clamping plates face upwards, and transverse rods of the clamping plates are connected with the connecting blocks; the two screw rods are oppositely and respectively in threaded connection with the vertical rods of the clamping and fixing plate; the human head model is provided with two simulated eye sockets, one simulated eye socket is a silica gel eye socket, and the replaceable eyeball is detachably connected with the silica gel eye socket; according to the utility model, most ophthalmological skill training and training can be satisfied by using a simple structure, and the cost and the occupied space of the eye training model are reduced.

The invention discloses a sparse electroencephalogram signal source positioning method based on functional magnetic resonance guidance, and relates to the crossing field of electroencephalogram signal processing and neuroimaging technologies. The method mainly comprises three parts of fMRI-guided sparse source space construction, subject specificity forward model construction and multi-target regularization inverse problem solving. The method comprises the following steps: firstly, screening high-activation voxels through BOLD signal intensity of fMRI, and constructing a sparse source space through connected component analysis and representative point selection; then, a subject specific boundary element (BEM) head model is constructed based on the structural MRI, and electrode registration and lead field matrix calculation are completed; and then a multi-target regularization model fusing data fidelity, space compactness and intensity consistency is constructed, optimal estimation of source current intensity is obtained through analysis and solution, and finally a positioning result of brain power activation is output. According to the method, the advantages of high time resolution of the EEG and high spatial resolution of the fMRI are fully played, the limitations of inverse problem morbidity, low spatial resolution and insufficient multi-mode fusion in traditional brain power supply positioning are effectively solved, and brain power supply positioning with high precision, noise resistance and high interpretability is realized; and a new scheme is provided for cognitive neuroscience research, nervous system disease diagnosis and brain-computer interface development.

The application discloses a 360-degree face head parameterization model generation method based on synthetic data, comprising the following steps: face alignment of diversified digital people is carried out by using Procrustes transformation, synthetic 3D face data sets with expression labels are shot and created; a 3DMM model with consistent topology is generated by using a principal component analysis method and Procrustes transformation, and model coefficients are obtained; a parameterized three-dimensional head model capable of generating multi-view multi-expression images is constructed and trained in combination with 3DMM coefficients and expression grid models; the model is fine-tuned to realize separation of hair and face, and image editing is carried out; expression coefficients in a video are extracted, and a digital head with dynamic expressions is generated through the model. The method improves the authenticity and expressiveness of head image generation, and enhances the capability of the model in generating dynamic expressions and multi-view images.

1. Name of the product in this design: Fan sunshade hat. 2. Purpose of this design: For sunshade and cooling. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model. 5. Other notes: The prosthetic head model shown in each view is a support and is not part of the scope of this design patent.

The application relates to the field of computer vision, and more particularly to a hair model generation method and system, an electronic device and a storage medium. The method comprises the following steps: obtaining a head shape base of a standard head model; obtaining a standard hair model; obtaining a hair shape base of the standard hair model according to the head shape base and the standard hair model; obtaining a shape coefficient of a target head model, wherein the shape coefficient is obtained according to a target face image, and the target head model is obtained according to the standard head model, the head shape base and the shape coefficient; and obtaining a corresponding target hair model according to the hair shape base and the shape coefficient. The method can be used to generate a high-quality, high-matching-degree and high-flexibility hair model, and improve the generation efficiency of the hair model.

A modelling method for making a virtual model of a user's head includes operations of: acquiring a plurality of depth images of a user's head in different head poses; processing the acquired depth images; localising on the two-dimensional images first marker points corresponding to characteristics of the head; estimating the head by estimating the yaw, pitch and roll angles of the head and the positioning of the head along three axes of a reference system of Cartesian axes for each of the two-dimensional images of the depth images, performing a transformation of the head pose; projecting the first marker points located in the respective cloud of points; associating iteratively in pairs the clouds of points until obtaining a cloud of synthesis points; aligning the cloud of synthesis points; and deforming the statistical head model by means of a minimization algorithm of a predefined cost function.

This invention discloses a transcranial magnetic stimulation (TMS) system and method. The system includes a head data acquisition module, a stimulation subject simulation module, and a coil parameter recommendation module. The head data acquisition module acquires head data of the target stimulation subject, including scalp data, skull data, and brain tissue data. The stimulation subject simulation module, connected to the head data acquisition module, constructs a head model of the target stimulation subject based on the acquired head data. The coil parameter recommendation module, connected to the stimulation subject simulation module, generates coil structure test parameters and performs simulation tests on the head model based on preset stimulation parameters and coil structure test parameters to obtain test data. Based on the test data, a TMS coil adapted to the head model is determined. Through the technical solution of this invention, the technical effect of improving the compatibility between the TMS coil and the target stimulation subject is achieved.

1. The name of the design product: headscarf (Yanyulan). 2. The use of the design product: for decorative headscarf. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: perspective view. 5. The head model in the design picture is a prop and does not belong to the content of the protected design. 6. The bottom surface is not easy to see when in use, and the top view is omitted.

1. Name of the product in this design: Wig (White Snake). 2. Purpose of this design: For use in wigs. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model. 5. The top and bottom views of this design are for parts that are not easily seen or cannot be seen during use, and therefore are omitted. 6. The head model in the design drawings is an internal component and does not fall under the scope of the design for which protection is sought.