17 results about "Facial geometry" patented technology

Disclosed herein is a computing system and method configured for generating one or more personalized digital visual representations. An example computing system may be configured to receive, from a computing device, one or more photos or videos of the user, process the one or more photos or videos to determine at least facial geometry characteristics of a user face model, obtain at least facial geometry characteristics of a plurality of canon characters from a character face model, generate a fused face model to retain the facial geometry characteristics of the user face model and the character face model, generate one or more personalized digital visual representations based at least upon the fused face model, and transmit, to the computing device, the one or more personalized digital visual representations.

Disclosed herein is a computing system and method configured for generating one or more personalized digital visual representations. An example computing system may be configured to receive, from a computing device, one or more photos or videos of the user, process the one or more photos or videos to determine at least facial geometry characteristics of a user face model, obtain at least facial geometry characteristics of a plurality of canon characters from a character face model, generate a fused face model to retain the facial geometry characteristics of the user face model and the character face model, generate one or more personalized digital visual representations based at least upon the fused face model, and transmit, to the computing device, the one or more personalized digital visual representations.

Techniques are provided for measuring interpupillary distance (IPD) using a mobile device application that integrates with augmented reality (AR) eyewear. The mobile application guides users through a measurement process using the device's camera and sensors to capture facial data. Computer vision algorithms analyze the data to determine IPD measurements while considering facial geometry and depth perception. The system provides real-time positioning feedback and allows manual entry of known IPD values. Measurements are stored in user profiles rather than on AR devices, enabling cross-device synchronization. The integration of IPD measurement into the initial device setup process, combined with flexible measurement options and profile-based storage, provides an accessible solution that maintains accuracy while eliminating the need for specialized measurement hardware.

The invention relates to a three-dimensional face high-fidelity texture generation method based on a multi-view high-definition image, and the method comprises the steps: constructing a three-dimensional face triangular mesh model through employing a camera fusion weight and an external parameter based on the cosine square of a view angle, and solving a texture mixed weight of each camera to a mesh triangular patch; the cylindrical UV expansion method is used for adapting to the geometrical characteristics of the human face, so that the texture stretching distortion can be obviously reduced; high-frequency detail reservation and low-frequency hue smooth transition are achieved through a frequency-band-divided texture fusion strategy, a high-quality texture source is optimized in cooperation with view angle cosine square weight and depth shielding detection, and fusion joints and detail dilution are avoided.

A facemask assembly can include an interior air filter that is replaceable and / or contains biocidal elements. The filter can capture exhaled H2O to activate silver ions creating a biocidal environment. In some embodiments, at least part of the facemask is made via additive manufacturing. A facemask frame assembly can create a pleated filter to increase surface area and bring the filter material closer to the mouth and nose. The facemask can include a facial skirt customized to the facial geometry of the wearer. The facemask can have a permanently sealed filter than can withstand boiling and autoclaving temperatures so the mask system can be sterilized without disassembly. In some embodiments, the facemask has a visible display of how many times the facemask has been sterilized. In some embodiments, the mask includes a RFID device that can transmit how many times the facemask has been sterilized.

A facemask assembly can include an interior air filter that is replaceable and / or contains biocidal elements. The filter can capture exhaled H2O to activate silver ions creating a biocidal environment. In some embodiments, at least part of the facemask is made via additive manufacturing. A facemask frame assembly can create a pleated filter to increase surface area and bring the filter material closer to the mouth and nose. The facemask can include a facial skirt customized to the facial geometry of the wearer. The facemask can have a permanently sealed filter than can withstand boiling and autoclaving temperatures so the mask system can be sterilized without disassembly. In some embodiments, the facemask has a visible display of how many times the facemask has been sterilized. In some embodiments, the mask includes a RFID device that can transmit how many times the facemask has been sterilized.

This application discloses a method, device, equipment, and medium for identifying food sensory preferences based on 3D facial micro-expressions, relating to the field of food sensory evaluation. This application first trains a teacher model. While ensuring the accuracy of the teacher model, a knowledge distillation strategy is used to transfer the teacher model to a student model, training a student model with stronger generalization capabilities. This allows a high-precision student model to be trained using a limited training set. This application applies 3D facial micro-expressions during the recognition process. Compared to 2D facial micro-expressions, this 3D facial micro-expression data has advantages such as stronger adaptability to lighting and head posture, as well as facial geometry association information and facial depth information, further improving the accuracy of food sensory preference recognition.

The present invention discloses a method for generating a singing video from a drama character picture based on a GAN network, including the steps of: 1. Collecting Qinqiang opera singing videos to synthesize a new dataset; 2. Locating the position of the face in the new dataset, cropping the video with the face as the center, and importing it into a depth perception generative adversarial network; 3. The facial depth network selects two consecutive frames from the opera videos in the training set and recovers the dense 3D facial geometry from the facial videos; 4. The facial depth network generates respective depth maps for the RGB image of the drama makeup and the RGB image frames of the opera videos, connects the depth maps with the corresponding RGB images to form RGB-D, and the facial key point detection network outputs K facial key points; 5. Generating distorted features; 6. Generating refined distorted features of the image; 7. Decoding the refined distorted features to generate an image; 8. Using the mimsave function to convert the image into a video and adding sound with ffmpeg to generate a singing video, making the expressions of the drama makeup characters in the video natural and coherent.

This disclosure relates generally to methods and systems for emotion-controllable generalized talking face generation of an arbitrary face image. Most of the conventional techniques for the realistic talking face generation may not be efficient to control the emotion over the face and have limited scope of generalization to an arbitrary unknown target face. The present disclosure proposes a graph convolutional network that uses speech content feature along with an independent emotion input to generate emotion and speech-induced motion on facial geometry-aware landmark representation. The facial geometry-aware landmark representation is further used in by an optical flow-guided texture generation network for producing the texture. A two-branch optical flow-guided texture generation network with motion and texture branches is designed to consider the motion and texture content independently. The optical flow-guided texture generation network then renders emotional talking face animation from a single image of any arbitrary target face.

Systems and methods to custom-design gaskets for a virtual reality (VR) interface, wherein the VR interface includes a head mounted display (HMD) to be worn by users are disclosed. Exemplary implementations may obtain facial geometry information for a user's face; generate a representation of the surface of the user's face, based on the facial geometry information; align the representation with a representation of the HMD; generate a model of a three-dimensional gasket that fits between the representation of the surface of the user's face and the representation of the HMD; export and / or present the model of the three-dimensional gasket; and / or perform other steps. Such custom-designed gaskets may provide an improved fit with better optical alignment when compared to mass-produced gaskets.

A three-dimensional head model generation method based on 2D facial expression analysis includes four steps of expression analysis, occlusion processing, multi-angle image generation and 3D model optimization. First, the expression parameters are extracted by the expression recognition model, and the expression is neutralized to generate expressionless images. Then, the image segmentation and deep learning inpainting technology are used to automatically identify and remove the occlusion, and the facial texture continuity is maintained. Then, multi-angle views are generated from the unoccluded neutral expression images to ensure the consistency of facial geometry and texture. Finally, the differentiable rendering technology is used to optimize the shape and map of the 3D model, realizing high consistency with the 2D image, so as to obtain high-precision and high-fidelity 3D head model. The multi-angle optimization method combines differentiable rendering with deep learning to improve the accuracy and consistency of 3D model generation. The neutral expression generation reduces geometric distortion, and the automatic removal of occlusion effectively improves the accuracy of facial reconstruction. It has strong practical value.

Disclosed herein is a computing system and method configured for generating one or more personalized digital visual representations. An example computing system may be configured to receive, from a computing device, one or more photos or videos of the user, process the one or more photos or videos to determine at least facial geometry characteristics of a user face model, obtain at least facial geometry characteristics of a plurality of canon characters from a character face model, generate a fused face model to retain the facial geometry characteristics of the user face model and the character face model, generate one or more personalized digital visual representations based at least upon the fused face model, and transmit, to the computing device, the one or more personalized digital visual representations.

Abstract A patient interface, such as a nasal cannula, for delivering breathable gas to a user is disclosed. The interface includes a body configured to be positioned on a user’s face and one or more nasal prongs fluidly connected to a gas supply for insertion into, or directing gas toward, the user’s nares. The body incorporates at least one force- or movement-responsive element configured to react to forces or movements experienced in a first region of the interface. The element is deformable or articulated and operates to isolate, absorb, dampen, or otherwise reduce transfer of such forces or movements to other regions of the interface. This localised response stabilises the position of the nasal prongs relative to the nares, maintaining a desired therapy delivery configuration despite external disturbances or changes in facial geometry. The responsive element may comprise hinges, pivots, joints, or regions of preferential flexibility or deformation, and may be arranged, for example, in a bridge region between body portions. Multiple elements may be combined to provide coordinated responses. The interface thereby enhances comfort and positional stability during use. Abstract

The present invention proposes a three-dimensional face reconstruction method based on a depth-guided two-stream network, constructs an end-to-end depth-guided two-stream network, and improves the robustness and generalization in complex environments. This method integrates image and depth prior information to enhance the performance of the reconstruction system under complex backgrounds, extreme lighting and large postures. Specifically: a facial geometry perception module is designed to generate accurate facial masks using image semantic features and depth priors to suppress background interference; a bidirectional cross-attention module is introduced to achieve efficient fusion of RGB and depth information and enhance feature representation capabilities; key modules work together to alleviate depth ambiguity problems, generate high-quality UV position maps and texture maps, and obtain high-precision three-dimensional face representations. This method outperforms mainstream methods in multiple evaluation indicators, especially in difficult scenes such as complex backgrounds, verifying the effectiveness, robustness and application potential of the framework, and providing technical innovation and practical value for face reconstruction in extreme environments.

The present invention discloses a video processing method, system and related devices based on a role avatar model. Among them, the above method includes: obtaining a driving video, permission verification information and corresponding driven object of a driving object; when the permission verification information of the driving object meets the permission verification conditions of the driven object, obtaining the role avatar model and reference image of the driven object; obtaining multiple frames of facial geometry rendering images corresponding to the driving object according to the driving video; obtaining time codes corresponding to each facial geometry rendering image, and generating a driven video through the role avatar model according to the reference image, each facial geometry rendering image and the time codes corresponding to each facial geometry rendering image. In the driven video, the driven object performs the same expressions and postures as the driving object in the driving video. The present invention uses the video of the driving object to drive the role avatar model, which is beneficial to improving the video display effect of the role avatar model.

The application discloses a kind of fusion visible light and infrared image live face detection method and system, it is first through parallel network in the extraction visible light and infrared feature, generate a face semantic mask chart that can accurately segment out eye, nose and other key areas simultaneously.Secondly, using the mask chart as anchor point, guide model to the regionalization feature pooling of visible light and infrared feature map, to obtain each semantic region independent, aligned feature vector.Finally, through cross-modal attention mechanism, these regional features are compared one by one, and through inconsistency amplification module to actively find and highlight the region that texture and temperature distribution do not match.This method forces the model to perform fine-grained logical verification, ensuring that the heat distribution accurately matches the facial geometry, thereby effectively identifying high-level fake attacks with temperature distribution that do not match real physiological features.

The present invention discloses a high-fidelity voice-driven digital human synthesis method based on 3DGS. First, a static digital human model is trained, constructed based on 3D Gaussian Splatting, and the image quality is improved using a spatial discriminator to capture the basic shape and appearance of the digital human. Subsequently, a dynamic driving network is trained, which includes an optimizable global prompt, a progressive conditional attribute prediction network module, and a dual discriminator architecture. Among them, the optimizable global prompt module is used to stabilize the facial geometry of the digital human and prevent drift during the animation process; the progressive conditional attribute prediction network module is used to efficiently and temporally coherently predict the dynamic Gaussian parameters of the digital human model; the dual discriminator architecture module is used to improve the realism and temporal consistency of the synthesized digital human animation. The present invention is applicable to voice-driven digital human animation synthesis, can effectively improve the realism, efficiency, and structural coherence of the synthesized digital human animation, and achieve real-time rendering.