59 results about "Face contour" patented technology

The embodiment of the invention provides an image processing method and a model training method. The image processing method comprises the steps that a face image of a digital person to be generated and a template face image are acquired, and the template face image comprises five sense organ template information and facial contour template information; based on the five-sense-organ template information, acquiring a facial five-sense-organ mask in the facial image of the to-be-generated digital human; based on the face contour template information and the face image of the to-be-generated digital person, determining a face contour of the to-be-generated digital person; and rendering the mask of the five sense organs of the human face to the facial contour of the to-be-generated digital human, and generating a human face image of the digital human. Through the image processing method provided by the invention, the efficiency of the digital human generation process and the personalized features of the digital human generation result are improved.

The application discloses a feature-consistent real face style transfer method and device for digital clothing sample display and a storage medium. The method comprises the following steps: constructing a rendering style face dataset DRFHQ; under the constraint of a face contour and a color tone, a rendering style face generator StyleGAN2-DRFHQ is obtained by fine-tuning a StyleGAN2-FFHQ generator using the DRFHQ; based on the StyleGAN2-DRFHQ, an e4e-DRFHQ encoder is obtained by fine-tuning an e4e-FFHQ encoder using the DRFHQ; a target rendering style face image is obtained from a digital clothing sample display image and is input into the e4e-DRFHQ encoder; a hidden code is obtained by inputting the target rendering style face image into the e4e-DRFHQ encoder; the hidden code is input into the StyleGAN2-FFHQ to generate a real face image; and the real face image is pasted back into the digital clothing sample display image.

The invention provides an intelligent partitioned traditional Chinese medicine precise skin care fumigation system based on multispectral face diagnosis and a phototherapy mask thereof, and belongs to the technical field of face care. Comprising a spectral imaging module which is used for acquiring a corresponding ultraviolet image, a visible light image, a near-infrared image and a thermogram, and identifying and positioning a facial contour and key points; the image preprocessing module is used for carrying out noise reduction and resolution optimization on the ultraviolet image, the visible light image, the near-infrared image and the thermal image; the data acquisition module is used for constructing a face state data set; and the face condition analysis module is used for establishing a skin state coefficient of the ith area according to the face state data set, and establishing a face comprehensive skin state coefficient according to the skin state coefficient of the ith area. The system can automatically generate a targeted skin care scheme, including phototherapy power adjustment and fumigation temperature and humidity control, so that partitioned, graded and refined nursing is realized, and the nursing effect is improved.

The invention relates to a calibration device for ophthalmology imaging equipment, and relates to the field of ophthalmology imaging related technologies, and the calibration device comprises an imager, a head bracket, a movable support frame, a jaw support, a forehead support, a linkage mechanism and a calibration mechanism. When a patient needs to finely adjust the head angle due to discomfort, the jaw support cannot rotate along with the patient, local pressure concentration is easily caused, friction burning pain is generated, and the adaptability of the patient is affected; secondly, symmetrical straight line clamping or simple cushion block supporting is mostly adopted for lateral positioning, adaptability to face contour changes of cheekbones, jaw bones and the like is lacked, and positioning deviation or oppression discomfort is easily caused; and thirdly, the problems that the existing device lacks a multi-direction linkage automatic calibration mechanism, manual intervention is needed for multiple times in operation, the calibration precision and efficiency are low, and the alignment requirement of high-precision ophthalmology imaging is difficult to meet are solved.

The utility model provides a kind of liquid storage cup face contour detection tool tool, to detect the bevel profile of liquid storage cup, the liquid storage cup includes first cup body and second cup body, the connecting surface of first cup body with second cup body is bevel, the liquid storage cup face contour detection tool tool includes: mounting seat, the upper surface of mounting seat is the bevel parallel with the connecting surface of liquid storage cup, the limiting slot for second cup body is placed into is opened in mounting seat, when second cup body is placed into limiting slot, first cup body is located outside limiting slot, and first cup body is higher than the upper surface of mounting seat;Resist component, resist component is located above installation component, to press the liquid storage cup in the limiting slot of mounting seat. The utility model's liquid storage cup face contour detection tool tool can realize the surface profile detection of liquid storage cup, detect conveniently, and efficiency is high, and the requirement to environment is low, and once investment can be reused.

The invention discloses a self-adaptive pressure sore preventing breathing mask, and relates to the technical field of breathing masks, the self-adaptive pressure sore preventing breathing mask comprises a main body mechanism, the main body mechanism comprises a mask main body, a soft cushion is fixedly mounted on the bottom surface of the mask main body, two mask buckles are fixedly mounted on each of the two side surfaces of the soft cushion, and a mask adjusting mechanism is arranged in the mask main body; the mask adjusting mechanism comprises an air cushion adjusting unit, the air cushion adjusting unit is located in the mask body, and the air cushion adjusting unit is used for automatically adjusting the air inflation amount according to the facial contour. The air inflation flow of the first conveying pipe and the second conveying pipe is accurately controlled, the air inflation air cushions at different positions keep appropriate air inflation volume, the air inflation air cushions at different positions are adjusted, it is ensured that the mask is tightly attached to the face, and the pressure of the local position can be independently adjusted.

The utility model provides a swimming goggles protection pad. The swimming goggles protection pad comprises a body; the swimming goggles are made of solid plastic or rubber soft materials, the hardness level is shore A10-20 Shore hardness units, the swimming goggles are provided with an assembling and connecting part fixedly connected with the swimming goggles and a face attaching part making contact with the face, the face attaching part is provided with a first circumferential face and a second circumferential face which are in a wave outline shape, and the wave outline of the first circumferential face is the outline of the upper half portion of an eye socket. The wave profile of the second peripheral surface is the lower half profile of the eye socket, so that after the swimming goggles are assembled on the swimming goggles to wear, the first peripheral surface and the second peripheral surface can be matched with the design of the wave profiles of the first peripheral surface and the second peripheral surface due to the characteristic that the solid soft material is easy to deform; the upper edge and the lower edge of the face fitting part are naturally matched with the peripheries of eye sockets of users with different face contours, and the effects of being comfortable to wear and free of water seepage are achieved.

This application discloses a method, apparatus, device, and storage medium for generating dynamic human images, belonging to the field of visual recognition technology. The method includes: processing video images of the face and body parts of a person engaged in conversation within a vehicle using a target face recognition model and a target body recognition model to obtain facial feature points and body part feature points; determining the position coordinates of facial reference points and body part reference points in a two-dimensional animation vector image based on the position coordinates of the facial and body part feature points; determining the facial contour curve and body contour curve in the two-dimensional animation vector image based on the position coordinates of the facial and body part reference points; and determining the two-dimensional animation of the person engaged in conversation based on the facial and body contour curves in the two-dimensional animation vector image. Two-dimensional animation has a smaller data volume than video, reducing the requirements for memory, transmission capacity, and transmission costs of in-vehicle equipment.

The invention belongs to the technical field of respiratory protection equipment, and discloses an intelligent sensing monitoring and automatic replacement type respiratory protection device and method.The intelligent sensing monitoring and automatic replacement type respiratory protection device is characterized in that massive face data are analyzed and modeled by means of a 3D printing technology and an AI algorithm, and a shell assembly fitting a face contour skeleton is printed according to human face structural features; mechanical energy-electric energy is converted into static charges on the surface of a filter material of the shell assembly for self-supply, and the friction nano-generator adsorbs and captures tiny particles; and the integrated sensing chip bin is used for automatically sensing and responding to the change of breathing resistance of a wearer and the accumulation condition of the filter material in combination with multi-mode sensing, performing early warning in time, automatically replacing the filter material, automatically adjusting the filtering working state of the filter material of the shell assembly and completing the replacement of the filter material. According to the invention, a friction nanometer power generation technology is innovatively introduced, so that the adsorption effect on tiny particulate matters is improved, and the dust and poison capturing efficiency is remarkably improved.

Embodiments of the present application provide a face customization method and device, electronic equipment and readable medium, the method comprises: obtaining a face contour model and at least one facial feature model; merging contour vertex information of the face contour model with facial feature vertex information of the facial feature model to obtain face vertex information of a face model; merging contour texture maps corresponding to the face contour model with facial feature texture maps corresponding to the facial feature model to obtain a face texture map corresponding to the face model; and rendering the face model using the face vertex information of the face model and the corresponding face texture map. The face customization function with greater customization range and higher degree of freedom can be provided for the user, and the face customization effect can be better.

The invention discloses an emotion recognition method and device, equipment and a storage medium. According to the method, image segmentation is carried out on a part of a face image of a user based on a preset image segmentation model, a complete face contour segmentation map of a current frame is obtained, and the part of the face image is an image formed by shielding a part of the face after the user wears the wearable device; constructing a space-time sequence based on the complete face contour segmentation map of the current frame and the complete face contour segmentation map of the historical frame; and performing emotion recognition on the space-time sequence based on a preset expression prediction model to obtain an emotion category of the user. Compared with a traditional emotion recognition method which cannot finish accurate recognition of the user emotion under the condition that the face is shielded, the method has the advantages that the full face expression in the equipment wearing scene is tracked through the pre-constructed image segmentation model and the expression prediction model, accurate emotion recognition is achieved, and the cross-user generalization ability is improved.

This invention discloses an image processing method, apparatus, storage medium, and program product. After acquiring an infrared image and a depth image with corresponding pixel relationships, the method first performs face detection on the infrared image to obtain a face detection bounding box for the target face. Then, the face detection bounding box is mapped onto the depth image to obtain the target coordinate information of the face detection bounding box in the depth image. Next, based on the target coordinate information, the face region is extracted from the depth image to obtain a depth map of the target face region. Then, contour fitting is performed on the target face in the depth map of the face region to obtain a face contour curve frame, which is then used for subsequent image processing. This invention can improve the accuracy of face region detection under uneven ambient lighting conditions, thereby improving the adjustment effect of FaceAE processing. This invention can be widely applied to image processing technologies in various scenarios such as cloud technology, artificial intelligence, intelligent transportation, and assisted driving.

The embodiment of the present application provides a face detection method and related equipment, through when detecting that the complete face contour of a user is in the acquisition range, image acquisition is performed on the face of the user, and a face image of the user is obtained; feature extraction is performed on the face image, overall face features and local face features are obtained; the overall face features are compared with overall face reference features, the local face features are compared with local face reference features, and feature difference information is determined; and a face detection result is generated based on the feature difference information. In the embodiment of the present application, the complete face image of the user can be acquired based on the wearable device, and the overall face features and the local face features are extracted from the face image. In the process of detecting the face and generating the face detection result, the overall face features and the local face features are comprehensively considered, and the subjective judgment of the doctor is not needed, so that the detection accuracy can be effectively improved.

The application relates to the field of artificial intelligence technology and discloses a non-sensing user identification and self-adaptive training method and system based on an AI display screen, which comprises the following steps: collecting a front face image and a human body posture video of a user by a visual sensor of an AI display screen of a sports device in a non-sensing mode; after extracting a part-related descriptor of a human face contour region in the front face image, generating face texture features corresponding to the user, and determining a user identity corresponding to the user; extracting skeleton key point data in the human body posture video to determine a joint position and a limb angle of the user, and analyzing action standardization of the user; collecting physiological feedback signals and behavior performance data of the user in real time by using an auxiliary sensor in the AI display screen, analyzing physiological fatigue of the user, and performing self-adaptive training and adjustment on sports parameters of the sports device to obtain an adjustment result. The application can improve the accuracy of non-sensing user identification and self-adaptive training based on the AI display screen.

The invention provides an identity recognition method which can be applied to the technical field of biological recognition. The identity recognition method comprises the following steps: acquiring a plurality of frames of to-be-processed images containing a face region of a to-be-recognized object; performing dynamic feature extraction on the multiple frames of images to be processed to obtain a local optical flow graph representing the facial micro-action of the object to be recognized and a target feature graph representing the semantic representation of any frame of image to be processed in the multiple frames of images to be processed; performing spatial feature extraction on any frame of to-be-processed image in the plurality of frames of to-be-processed images to obtain a facial contour feature map representing the spatial position of the facial region of the to-be-recognized object in the to-be-processed image; performing feature fusion on the local optical flow graph, the target feature graph and the facial contour feature graph to obtain a fused feature graph; and inputting the fused feature map into a pre-training recognition model to obtain an identity recognition result of the to-be-recognized object. The invention further provides an identity device, equipment, a storage medium and a program product.

The invention discloses a fatigue driving detection method, system and device and a medium, and the method comprises the steps: collecting a driving image of a driver, carrying out the preprocessing of the driving image, and recognizing a mask shielding state; positioning facial features of the driver, locking eye angular point positioning based on a facial contour, intercepting eye and mouth area images, sending the area images into a built identification model, and obtaining eye states and mouth states; according to the eye state and the mouth state, the fatigue degree of the driver is recognized by fusing multi-dimensional data, and driving reminding is given based on the recognition result. According to the method, the eye and mouth areas are positioned through the face frame and eye corner coordinates, the eye and mouth area images are intercepted and corrected, and the images are used as input to be transmitted to the eye and mouth state recognition model constructed based on the convolutional neural network, so that the fatigue degree of a driver is recognized, the traffic accident risk is effectively reduced, fatigue driving is avoided, and the driver experience is improved. And the occurrence rate of traffic accidents is reduced from the source.

The invention discloses a facial expression tracking method, a facial expression tracking model training method, electronic equipment, a storage medium and a computer program product, and relates to the technical field of image processing, and the method comprises the steps: taking each frame of facial image in multiple frames of facial images continuously collected from a target object as a first target image, acquiring a first face image sequence corresponding to the first target image; inputting each frame of face image in the first face image sequence into a preset face contour segmentation model for segmentation to obtain each binary frame of first face contour image; the first contour image sequence including the first facial contour images is input into a preset facial expression tracking model for prediction, facial expression features corresponding to the first target image are obtained, and convolution operation in the facial expression tracking model is 3D convolution operation performed in three dimensions of time, width and height. According to the invention, the accuracy of the facial expression features extracted in the facial expression tracking technology is improved.

The application relates to a face recognition method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a face image of a to-be-recognized object, and extracting a planar feature and a depth feature from the face image; performing first amplification processing on the planar feature to obtain an amplified planar feature used for enhancing face contour details of the to-be-recognized object; performing fusion processing on the amplified planar feature and the depth feature to obtain a fusion feature map of the face image; performing second amplification processing on the fusion feature map to obtain an amplified fusion feature map used for enhancing face dynamic change details of the to-be-recognized object; and performing face recognition based on the amplified fusion feature map to obtain a face recognition result of the to-be-recognized object. The method can extract detailed features in the face image, and can perform face recognition according to the detailed features, so that the accuracy and efficiency of face recognition can be improved. Moreover, the method can save training costs in the case of scarce face image data.

The utility model discloses a cold compress cooling mask applied after medical cosmetology. The cold compress cooling mask comprises a cold compress cooling mask body used for covering the face of a patient after medical cosmetology. The cold compress cooling mask body comprises a cold compress mask base layer which is the same as the face contour of a patient, and an eye area, a nose area and a mouth area are arranged on the cold compress mask base layer and located at the positions of the eyes, the nose and the mouth of the patient respectively. The cold-compress facial mask is reasonable in overall design, simple in structure and convenient to operate, the cold-compress cooling layer and the water film layer are arranged, heat of the cold-compress cooling layer can be transmitted to the water film layer through the cold-compress facial mask base layer, the water film layer can be effectively attached to the face of a patient, and the face of the patient can be effectively protected by means of effective combination of the cold-compress cooling layer and the water film layer. The face of a patient can be subjected to effective cold compress, the comfort of the face of the patient in the cold compress process can be effectively improved, and great convenience is brought to cold compress cooling work of the patient after medical beauty.

The invention discloses a multifunctional facial makeup instrument, belongs to the field of intelligent wearable equipment, and aims to solve the problems of sound quality distortion of a traditional sound box, positioning effect in a head-mounted earphone head and single function and insufficient experience of existing portable facial massage and hypnosis equipment. The device comprises a facial makeup main body matched with a facial contour, an audio playing module, a facial massage module and an adjustable earphone assembly, the audio playing module eliminates the positioning effect in the head and keeps the high-fidelity tone quality by means of air-guided sound waves of a rear shell sounding horn in combination with facial bone conduction; the face massage module realizes full face massage with adjustable frequency and adjustable force through a vibrator in a facial makeup; the earphone assembly insulates noise, plays guide audio and forms a mental intervention and hypnosis system in combination with massage; the equipment supports independent or synchronous work of three functions, a vibration mode is intelligently matched with an audio frequency band during synchronization, high-fidelity audition, efficient facial rehabilitation and deep mental intervention are realized through multi-mode fusion, and the equipment is comfortable to wear and convenient to use.

The utility model discloses a protective mask for isolating poisonous and harmful reagents, relates to the technical field of safety protection, and solves the problems that if an attaching layer of an outer frame edge is difficult to effectively attach, a gap is formed between a human face and a gas mask, even if the gap is only a tiny gap, the gap can become a breakthrough opening of harmful gas, and the safety of the human face is affected. In order to solve the problems that toxic gas can permeate into the mask body quietly along gaps, and respiratory diseases are easily caused for a long time, the mask comprises a mask body, a reinforcing mechanism comprises a notch and a spring, and the other end of the spring is fixedly provided with an attaching pad. The reinforcing mechanism is additionally arranged, and the attaching pad is fixedly connected with the notch through the spring installed at the bottom end of the attaching pad; under the ingenious effect of elasticity, the gas mask can be flexibly adjusted according to different facial contours and closely close to the face, and therefore the situation that a gap is formed between the human face and the gas mask and is sufficient to become a breakthrough opening of harmful gas when the gas mask is difficult to effectively fit can be effectively prevented.

The present disclosure provides a face contour key point determination method and device, equipment and storage medium, and relates to the technical field of computers, to at least solve the problem of large data volume in related art face contour key point processing. The method comprises: obtaining a face image to be detected; determining a face contour region on the face image; performing first mapping processing on the face contour region on the face image to obtain a face contour image with a standard shape; determining first key points on the face contour image; the first key points are key points of the face contour on the face contour image; performing second mapping processing on the first key points on the face contour image to obtain second key points; the second key points correspond one-to-one to the first key points; and the second key points are key points of the face contour on the face image.

The invention relates to a living body recognition method based on binocular infrared face detection. The method comprises the following steps: acquiring infrared image data in different illumination states through linkage of a binocular infrared camera and an LED light supplementing assembly; positioning the position of a face frame in continuous frames, and extracting dark channel data in the frame; calculating an inter-frame face position offset, and comparing a preset threshold to obtain a comparison identifier; calculating depth-of-field data in combination with the comparison identifier and the dark channel data, and obtaining a binarized depth-of-field image through binarization; extracting a face contour, and comparing the contour perimeter with a preset threshold to obtain a contour set conforming to the size; polygon approximation is carried out on the contour set, the number of vertexes is obtained and compared with a preset threshold interval, and candidate face depth-of-field images are obtained; gradient information is obtained through edge detection, weighting calculation is carried out by presetting a face outer side weighting point and giving a weight, and a preset living body threshold value is compared through normalization operation, so that living body recognition based on binocular infrared face detection is realized.

A face image rotation method, device and storage medium, the method comprises the steps of: acquiring three-dimensional face data; constructing a three-dimensional face model database according to the three-dimensional face data; training a deep convolutional neural network using the three-dimensional face data; generating a rotated two-dimensional face grayscale image according to the deep convolutional neural network; and generating a rotated two-dimensional face color texture image using style transfer rendering according to the two-dimensional face grayscale image. The face image rotation method, device and storage medium provided by the application rely on a neural network model focusing on three-dimensional face model shape parameter regression, can improve the accuracy of rotating face shape structure, and retain face deep features; the style transfer adversarial neural network is used to extract face decoupling features, which can well render the high-frequency details of the rotated face; while ensuring the accuracy of the rotated face contour positioning feature, the face texture color and high-frequency details can be accurately rendered, and the face deep features are retained.

This utility model relates to the field of facial mask technology and discloses a hydrophilic moisturizing facial mask base fabric, including a mask base sheet. Connecting mechanisms are installed on both sides of the mask base sheet. Multiple tear grooves are provided on the outer surface of the mask base sheet. Two adhesive strips are fixedly connected to both sides of the mask base sheet. The connecting mechanism includes two connecting ropes. An air pump is fixedly connected to one side of each connecting rope. A connecting tube is fixedly connected to one side of the air pump. A telescopic tube is fixedly connected to one side of the connecting tube. A delivery tube is fixedly connected to the other end of the air pump. A leakage component is provided on the outer surface of the mask base sheet. In this utility model, the connecting ropes and adhesive strips effectively fix the mask base sheet, ensuring a close fit to the face. The design of the air pump and telescopic tube allows the mask base sheet to adjust according to the facial contours during use, enhancing the fit.

The utility model relates to the field of anaesthetic masks, in particular to an anaesthetic mask not easy to loosen, and aims to solve the technical problems that the anaesthetic mask is not easy to fix and can loosen or fall off after a long time to cause emergencies and increase treatment risks. Comprising a wearing assembly, an auxiliary assembly, a fixing assembly, an anaesthetic mask body and a breathing tube. The anesthetic mask body can be quickly fixed to the mouth and nose of a patient through the wearing assembly, the whole anesthetic mask body is attached to the face contour of the patient through the auxiliary assembly, the situation that anesthetic gas leaks due to the fact that a gap exists between the face contour and the anesthetic mask body is avoided, the patient is better assisted in inhaling gas, and the anesthetic effect is improved. The fixing assembly can help various patients to wear the anaesthetic mask body and stably keep the anaesthetic mask body, the possibility of loosening or even falling off due to too long time is avoided, and the problems that the anaesthetic mask is not easy to fix and can be loosened or fall off due to long time, and the treatment risk is increased due to emergencies are solved.

The application relates to an unpaired face-to-face expression editing method based on an adversarial generation, and belongs to the field of image generation of deep learning. The method extracts an expression-related face contour graph from a face through a special expression segmentation model, so that expression constraint input to a generator is more accurate, and then improved expression consistency loss and an attention mechanism are used to further ensure that edited expressions can retain more identity information and are not distorted.

The application discloses a method for generating fake data for a DeepFake authentication model, which comprises the following steps: performing face detection on an input image to extract a face image; generating a face contour based on the input face image; searching for a face contour in a face database that matches the face contour to a threshold; extracting an inner region of the face contour of the input face image and an outer region of the matched face contour in the face database; and fusing the inner region of the face contour of the input face image after smoothing and compression with the outer region of the matched face contour in the face database to generate fake face data with artifact information. The application can realize the rapid generation of fake face data and meet the training needs.

The application belongs to the field of laryngeal mask processing, and particularly relates to an individualized laryngeal mask processing method based on an Ai vision model: input and size calibration: collecting multi-view photos of the head and neck of a patient, calibrating the pixel size and the actual size, and obtaining a scale factor of each photo. External morphological feature vector: quantifying the scale factor of each photo and the head and face contour into an external morphological feature vector x. Laryngeal mask parameter set generation and definition: defining a laryngeal mask structure parameter set P, and converting the external morphological feature vector into a laryngeal mask parameter estimate value and an uncertainty index by using a mapping model of the Ai vision model. Geometric constraint and safety margin correction: applying geometric, manufacturing constraints and safety margins to the parameters to obtain final parameters. Geometric modeling: based on constructing a laryngeal mask integrated function model, deriving a 3D printing file and printing a finished product, and ensuring model adaptation and accurate position.