29 results about "Face model" patented technology

The application relates to the technical field of CAE preprocessing and cloud cooperation, and discloses a lightweight CAE geometry engine and a cloud real-time cooperation method and system. A cloud server acquires an original CAE geometry model, performs topological simplification and data compression on the original CAE geometry model, and generates a lightweight geometry data file containing multiple resolution levels; the cloud server pushes the received difference data packet to other online cooperation terminals; the other cooperation terminals parse the unique version number carried by the difference data packet through a locally loaded WebAssembly geometry engine module, and perform operation replay updating on the local geometry model according to the differential data contained in the difference data packet. According to the scheme, the original CAE model data volume is reduced by 90%-95%, the WebAssembly engine realizes a 100,000-face model rendering frame rate of 30-60 fps, and the operation response delay is less than or equal to 100 ms, thereby breaking through the performance bottleneck of browser-side geometry processing.

The application provides an expression tracking method and device, equipment and storage medium, relates to the computer vision field of artificial intelligence, and the method comprises the following steps: obtaining a neutral face model of a target person and M expression bases BS corresponding to the neutral face model, M>0; collecting the face of the target person in multiple view directions to obtain multiple current images corresponding to the multiple views respectively; using an expression tracking algorithm, calculating M BS coefficients corresponding to the M BSs respectively for tracking the facial expressions in the multiple current images; based on the neutral face model, the M BSs and the M coefficients, constructing tracking images of the multiple current images. The expression tracking method provided by the application can improve the expression tracking effect.

The application discloses a face image face filling method and system and a storage medium, and the method comprises the following steps: acquiring an input image, performing face feature extraction, and obtaining two-dimensional face features; obtaining two-dimensional face texture feature information according to the two-dimensional face features, and calculating the illumination coefficient of the input image; performing three-dimensional face reconstruction based on the two-dimensional face features and the two-dimensional face texture feature information, combining a preset three-dimensional face model, obtaining a first three-dimensional face model; performing morphological filling processing on the first three-dimensional model, obtaining a second three-dimensional face model, and then adding the illumination coefficient to obtain a third three-dimensional face model; and mapping the third three-dimensional face model to a two-dimensional plane to obtain a face image face filling effect diagram. Through the three-dimensional face reconstruction and morphological filling processing based on the preset three-dimensional face model, the filling effect diagram is more realistic, natural and stereoscopic, and the user can comprehensively evaluate the risk of medical beauty filling.

The application discloses an intelligent display control method and system for liquid crystal panel image recognition driving, and relates to the technical field of liquid crystal panels. The method comprises the following steps: collecting user image data of a liquid crystal panel through a camera and preprocessing the user image data to obtain a user image of the liquid crystal panel; inputting the user image of the liquid crystal panel into an improved VGG-Face model to output a user age prediction value; collecting environment data of the liquid crystal panel, and based on the environment data of the liquid crystal panel and the user age prediction value, performing display adjustment on the liquid crystal panel through a fuzzy logic control method to obtain a first display adjustment result; collecting user feedback data, training a gradient boosting tree model by taking the user feedback data as a training set to obtain a trained gradient boosting tree model, inputting the first display adjustment result into the trained gradient boosting tree model, and outputting a second display adjustment result, so that intelligent display control of the liquid crystal panel is realized.

This invention discloses a dynamic face texture generation method based on facial expression semantic features, belonging to the interdisciplinary field of computer vision and graphics. It includes: extracting geometric parameters from a parametric face model tracking video, driving model deformation, and anchoring 3D Gaussian points; constructing a dynamic texture generation network, using an identity latent code as a basis, and modulating the texture feature map layer by layer using facial expression parameters through a feature modulation module to output a dynamic UV texture map; calculating the gradient magnitude of the UV texture map, and adaptively encrypting the Gaussian points based on the texture gradient and geometric gradient; obtaining Gaussian point attributes based on UV coordinate sampling, and inputting them into a differentiable rasterizer renderer after viewpoint-related color compensation to generate an image. This achieves dynamic texture generation that is linked to facial expressions, significantly improving the dynamic realism and detail fidelity of digital human reconstruction, and solving the problem of high-frequency dynamic detail loss caused by static texture representation in existing monocular video 3D face reconstruction.

A method performed by one or more network devices to execute one or more smart contracts stored in a blockchain for anonymizing a face appearing in digital media content. The method includes, for each of a plurality of users, obtaining a face model associated with the user, obtaining digital media content provided by a media platform, detecting one or more faces appearing in the digital media content, determining whether the detected face matches a face of any of the plurality of users based on applying one or more of the face models associated with the plurality of users to the detected face, anonymizing the detected face in response to a determination that the detected face matches a face of one of the plurality of users to generate an anonymized face, and providing the anonymized face to the media platform.

The application provides a method, device, equipment and medium for improving expression base expression capability, the method comprising: extracting initial semantic parameters of each frame of three-dimensional reconstruction data based on an initial expression parameterization model, and generating an initial parameterization result by driving a preset face model through a first expression base corresponding to the initial semantic parameters; comparing the initial parameterization result under each first expression base with the three-dimensional reconstruction data to determine whether the initial parameterization result and the three-dimensional reconstruction data match; if not, generating expression residual data according to error information of the initial parameterization result and the three-dimensional reconstruction data; adjusting the initial expression parameterization model using the expression residual data to obtain an adjusted second parameterization model, and driving the face model through a second expression base determined by the second parameterization model to generate a second parameterization result matching the three-dimensional reconstruction data. The application does not need manual input of external data, thereby improving efficiency.

The present disclosure relates to a model expression redirection method and device, storage medium and electronic equipment, and relates to the technical field of computers. The method comprises: obtaining a first linkage controller corresponding to a first linkage expression skeleton and a first secondary controller corresponding to a first secondary expression skeleton; creating a connection relationship between the first linkage controller and the first secondary controller, and calculating a mixing weight required for redirecting a first model expression from a first face model to a second face model according to the first secondary controller; calculating a constraint intermediate group required for redirecting the first model expression to the second face model based on the connection relationship, the mixing weight and the first secondary controller; generating a target skeleton based on the constraint intermediate group, and performing skin processing on the second face model according to the target skeleton to obtain a second model expression corresponding to the first model expression on the second face model. The present disclosure improves the redirection efficiency of model expressions.

The application discloses an analysis method and device for airflow movement distribution and virus distribution on a mask and a medium, relates to the technical field of public health, and comprises the following steps: constructing a three-dimensional face model and a mask model according to a three-dimensional modeling design software, and extracting an air domain formed by the mask and the face; performing computational fluid dynamics simulation on the air domain formed by the mask and the face by using a computational fluid dynamics software to obtain a simulation result; comprehensively analyzing the airflow movement distribution on the mask, and calculating a virus distribution rule of virus particles on the mask; and optimizing the material and structure of the mask based on the virus distribution rule. The application solves the problems that the design optimization of the mask structure is limited and the mask protection performance is low.

This invention discloses a deep learning-based image optimization method for self-service photo booths, comprising: generating a set of distorted face regions and calculating a comprehensive distortion eccentricity index for each distorted face region; calling an improved 3D Gaussian splash face model and loading it into a priori buffer to establish a 3D semantic prior template; obtaining a set of control point correspondences; calculating a set of control point displacement vectors based on the control point correspondences; constructing a thin-plate spline interpolation global mapping function weighted by the comprehensive distortion eccentricity index; mapping and solving all pixel positions of the original wide-angle distorted image data, and performing pixel-level remapping on the original wide-angle distorted image data to obtain corrected image data; and generating corrected output image data. This invention achieves structural consistency correction based on 3D semantic prior constraints, improving the realism of facial structure and the stability of facial feature proportions at wide-angle edges.

A method for generating a voice-driven digital human based on neural fields includes the following steps: S1, constructing a deformable digital face using a face model; S2, encoding the audio features of a given speech and mapping the audio features to the expression space of the digital face; S3, driving the digital human in the standard space based on the audio features according to neural field representation; wherein, the digital human in the standard space is obtained based on the neural occupancy field and the neural texture field, and for the spatial coordinates in the standard space, the corresponding displacement is output by the neural displacement field according to the audio features. Further, step S3 also uses facial semantics as an explicit control signal to perform eye control based on facial semantics. Compared with traditional methods, this invention can achieve more synchronized face and torso driving and eye opening / closing control, surpassing traditional methods in both image quality and speech synchronization metrics.

1. Name of the designed product: 3D fitting scanner. 2. Use of the designed product: for scanning face modeling and intelligently recommending lenses. 3. Design points of the designed product: in the combination of shape and pattern. 4. Picture or photo best indicating the design points: perspective view.

A face drive generation method based on neural radiance field includes the following steps: S1, extracting feature points of a face region from image frames of a video, calculating expression features and posture features of a corresponding three-dimensional face model according to the feature points, and extracting speech features from a speech part of the video; S2, for each position in a three-dimensional space where the three-dimensional face is located, predicting a mixed shape vector for controlling the three-dimensional face, a posture correction coefficient, and a linear mixed skinning weight through a neural network; S3, based on a deformation technology of the three-dimensional face model, calculating a deformed position of each current position according to the posture features and the speech features obtained in step S1 and the parameters predicted in step S2; S4, predicting a flow field according to each calculated position, aggregating feature information of adjacent time through a multi-frame set manner, and optimizing a face reconstruction loss by using time aggregation, so as to constrain smooth transformation of a dynamic neural radiance field in time. The method improves the accuracy of expression deformation, and makes the generated video more smooth and consistent.

The application discloses a kind of coal mine multi-scale data collaborative processing and model dynamic updating method and system, belong to coal mining technical field, this method includes the following steps: obtaining multi-scale data, constructs and contains different spatial levels multi-scale data set;Establish cross-scale constraint mapping;Extract current state feature of working face, and construct working face state prediction model according to cross-scale constraint mapping;The prediction error of working face state prediction model is calculated, and the prediction error is based on adaptive adjustment, and the dynamic updated working face state prediction result is obtained;Dynamic updated prediction result is reversely applied to working face production decision, and the feedback data generated by decision execution is reintroduced into the above steps.The application adopts the above method and system, constructs hierarchical organization multi-scale data set, so that the data of different spatial levels collaborates in the construction of working face model under the same framework, avoids the problem of multiple-source data fragmentation.

This invention relates to artificial intelligence technology, and its embodiments provide a method for building a 3D model based on 2D key points, a computer, and a storage medium. The method includes the following steps: acquiring a target 2D face image; performing predictive processing on the target 2D face image using a target 2D face key point recognition model to obtain a first key point image including target key points; performing 3D reconstruction processing on the target 2D face image to obtain a 3D texture image; performing coordinate transformation processing on the key point coordinates in the first key point image based on the texture map coordinate data of the 3D texture image to obtain a second key point image based on the texture map coordinate data; and building a target 3D face model based on the second key point image and the 3D texture image. This method can improve the accuracy of binding corresponding points in the 3D face model, making the built 3D face model closer to real-world usage scenarios.

This invention discloses a method, apparatus, and medium for facial expression binding based on marker point optimization. The method includes: annotating facial key points, eye contour points, and expression-independent regions of the input facial model in an input facial model and an expression template; deforming the input facial model to a neutral expression of the expression template based on the annotation results; establishing a correspondence between the mesh patches of the input facial model and the expression template after deformation; and sequentially performing deformation transfer on the input facial model based on the deformation of all expressions relative to the neutral expression in the expression template to generate a blended shape corresponding to all expressions, thus completing the facial expression binding task. This invention uses eye contour points for annotation and performs eye closure optimization based on the annotation of eye contour points during subsequent deformation transfer, effectively optimizing the performance of the expression binding method for closed-eye expressions. This invention can be widely applied in the field of facial image data processing.

The present disclosure provides a virtual model processing method and device and electronic equipment. Animation data of a reference face model is obtained; the reference face model comprises a plurality of reference model parts; each reference model part has at least one replaceable model part corresponding thereto; the skeleton of each reference model part corresponds to the skeleton of the replaceable model part; the animation data is used to control the skeleton of the reference face model to generate movement; a target model part is determined from the at least one replaceable model part; based on the target model part, the reference model part corresponding to the target model part in the reference face model is updated to obtain a target face model; the skeleton of the target face model is controlled to generate movement based on the animation data, and a display animation corresponding to the target face model is generated. This way enables the user to replace each part of the face model according to the requirement, and ensures that the animation display effect of the replaced face model is normal, thereby improving the user's face model shaping experience.

The application relates to a video image processing method and device, electronic equipment, computer readable storage medium and computer program product. The method comprises the following steps: acquiring a to-be-processed image including a face in a video; performing face feature extraction on the to-be-processed image to obtain a target face feature; determining a candidate face model matched with the target face feature, and determining a target face model according to the candidate face model and the target face feature; the candidate face model is a pre-established face model; and obtaining a target image according to acquired makeup effect parameter information and the target face model. The method can realize fast makeup.

Provided is an information processing apparatus including a display control unit and a fitting unit. The display control unit displays a distribution image indicating distribution of a plurality of marker points extracted from a face model of a performer in a superimposed manner on a face image of the performer. The fitting unit fits the face model to the face image by using position information of a placed marker each time the marker is placed on a face of the performer after the distribution image is superimposed, and adjusts a superimposed position of the distribution image based on a fitting result.

The disclosure discloses a three-dimensional face model reconstruction method and device, electronic equipment and readable storage medium, and relates to the technical field of computers, in particular to computer vision technology and graphics technology. The specific implementation scheme is: based on face images of at least two perspectives of a user, obtaining face key points of face images of each perspective in the at least two perspectives; using the face key points of the face images of each perspective, respectively performing parameter optimization processing on a parameterized three-dimensional face model to obtain a three-dimensional face model of each perspective; and performing model fusion processing on the three-dimensional face model of each perspective to obtain a reconstructed three-dimensional face model of the user.

The application provides an expression migration method, device, equipment and storage medium, and relates to the field of computer vision of artificial intelligence. The application obtains a topological alignment first mesh model and a topological alignment second mesh model of a target character by performing topological alignment on an original character and the target character; determines a point pair in mutual nearest neighbor relationship in the first mesh model and the second mesh model; determines a first anchor point of a first expression to which a first neutral face model of the original character is deformed; acquires a second anchor point of a second expression to which a second neutral face model of the target character is deformed according to the point pair in mutual nearest neighbor relationship and the first anchor point; and determines vertex coordinates of the second expression by using an expression migration algorithm with the first anchor point and the second anchor point as constraints. The application can adjust a deformation area based on a neutral face when performing expression migration between characters with different topologies, and ensure that the overall expression model after migration remains stable in relative position.

The application relates to a vehicle driver head posture monitoring method, which comprises the following steps: obtaining a driver face image through an infrared camera; extracting six 2D face key points based on the driver face image and marking 2D image coordinate points; building a 3D standard face model, extracting 3D standard face key points and marking 3D model coordinate points; solving a rotation matrix based on the 2D image coordinate points, the 3D model coordinate points, the focal length, the focal point and the distortion coefficient of the infrared camera; solving driver head posture Euler angles according to the rotation matrix; performing face three-dimensional angle regression according to the head posture Euler angles, judging whether the driver head posture changes or not; judging whether the driver exceeds a safe driving range according to the driver head posture change, if not, continuously monitoring; if yes, warning the driver; the application can monitor the driver head posture in real time, reduce the accident rate and ensure driving safety.