690 results about "Facial affect" patented technology

A method and system for detecting facial expressions in digital images and applications therefore are disclosed. Analysis of a digital image determines whether or not a smile and/or blink is present on a person's face. Face recognition, and/or a pose or illumination condition determination, permits application of a specific, relatively small classifier cascade.

A communication device may include logic configured to detect a request to initiate a video call by the user of the communication device; select an avatar for the video call, wherein the avatar corresponds to an image selected by the user to be used as a replacement for a video stream for video calls associated with the user; determine a facial expression associated with the user of the communication device; select an avatar facial expression for the selected avatar, based on the determined facial expression; and incorporate the selected avatar facial expression into a video stream associated with the video call.

The invention discloses an expression input method and device based on face identification, and relates to the technical field of input methods. The method comprises the steps of starting an input method, acquiring a shot picture of a user, determining emotion labels corresponding to the facial expression in the picture by a face expression identification model, acquiring the expressions of all themes of the emotion labels respectively based on the corresponding relation of the emotion labels and the expressions in all the themes, the expressions of all the themes are ordered and used as candidate items to be displayed in a client end. According to the expression input method and device, the labels can be directly identified and matched according to the currently-shot picture of the user, the user can input the expression conveniently, the expression accuracy is high, and rich and wide-range expression resources are provided for the user.

The invention discloses an expression cloning method and device capable of realizing real-time interaction with a virtual character and belongs to the fields such as computer graphics and virtual reality. The method includes the following steps that: 1, modeling and skeleton binding are performed on the virtual character; 2, the basic expression base of the virtual character is established; 3, expression input training is carried out: the maximum displacement of facial feature points under each basic expression is recorded; 4, expression tracking is carried out: the facial expression change of a real person is recorded through motion capture equipment, and the weights of the basic expressions are obtained through calculation; 5, expression mapping is carried out: the obtained weights of the basic expressions are transferred to the virtual character in real time, and rotation interpolation is performed on corresponding skeletons; and the real-time rendering output of the expression of the virtual character is carried out. With the method adopted, the expression of the virtual character can be synthesized rapidly, stably and vividly, so that the virtual character can perform expression interaction with the real person stably in real time.

The invention provides a method of micro facial expression detection based on a facial action coding system (FACS). The method has a main content of a visual CNN filter, network architecture and training, migration learning and micro facial expression detection. The method comprises steps: firstly, a robust emotion classification framework is built; the provided network learning model is analyzed; the provided network training filter is visualized in different emotion classification tasks; and the model is applied to micro facial expression detection. The recognition rate of the existing method in micro facial expression detection is improved, the strong correlation between features generated by an unsupervised learning process and action units for a facial expression analysis method is presented, the FACS-based function generalization ability in aspects of providing high-precision score cross data and cross mission is verified, the micro facial expression detection recognition rate is improved, the facial expression can be recognized more accurately, the emotion state is deduced, the effectiveness and the accuracy of application in various fields are improved, and development of artificial intelligence is pushed.

The invention discloses a classroom teaching effect evaluation system based on facial expression recognition. According to the invention, videos in a classroom are analyzed in real time; the facial expressions of students in class are extracted, and the understanding degree, the activity degree, the doubtful degree and the activity time index information of the students in class are counted and analyzed, so that teachers can know the psychological states of the students and the mastery degree of the students on the knowledge points, the teachers can adopt corresponding teaching regulation andcontrol means, and the teaching quality of the class is improved; The classroom expression state of the teacher is automatically analyzed, the classroom expression index of the teacher is counted, andthe classroom emotion basis is provided for teaching management personnel to examine the teacher. The classroom expressions of teachers and students are recorded, the classroom expression indexes ofthe teachers and the students are obtained through statistical analysis, and the indexes serve as reference indexes for classroom teaching evaluation and have comprehensiveness and objectivity. the classroom teaching effect of the target course in each school for course reform is counted as a reference. Through the technical scheme of the invention, teachers and teaching management personnel can better accomplish the teaching concept taking students as the main part.

The invention discloses simulated group interaction with multimedia content. A method and system for generating time synchronized data streams based on a viewer's interaction with a multimedia content stream is provided. A viewer's interactions with a multimedia content stream being viewed by the viewer are recorded. The viewer's interactions include comments provided by the viewer, while viewing the multimedia content stream. Comments include text messages, audio messages, video feeds, gestures or facial expressions provided by the viewer. A time synchronized commented data stream is generated based on the viewer's interactions. The time synchronized commented data stream includes the viewer's interactions time stamped relative to a virtual start time at which the multimedia content stream is rendered to the viewer. One or more time synchronized data streams are rendered to the viewer, via an audiovisual device, while the viewer views a multimedia content stream.

The invention discloses a prisoner psychological health state assessment method and a system based on multi-modal information. The method comprises the following steps: obtaining physiological signals, facial expression images and voice signals of reformed prisoners and prisoners to be tested after they experience virtual reality scenes, and extracting physiological signal features, facial expression image features and voice signal features from the obtained signals; inputting the physiological signal features, facial expression image features and voice signal features of the reformed prisonerinto a pre-trained neural network model, and outputting a psychological state assessment vector of the reformed prisoners; inputting the physiological signal features, the facial expression featuresand the voice signal features of the prisoners to be tested into a pre-trained neural network model, and outputting a psychological state assessment vector of the prisoners to be tested; calculating the psychological state assessment vector distance between the prisoners to be tested and the reformed prisoners; and assessing the mental health state of the prisoners according to the distance.

The present invention discloses an automatic music playing system and method based on target facial expression acquisition. The system comprises an acquisition unit, a processing unit and a music playing unit. The acquisition unit is used for acquiring video information of facial emotion of a user, and transferring the video information to the processing unit. The processing unit is used for controlling the acquisition unit to acquire a video of the user, integrating the acquired video information to generate a video signal, and extracting an emotion signal of the user from the video signal after integration, and transferring the emotion signal to the music playing unit. The music playing unit implements automatic playing of music according to a change of facial expression of the user. According to the system and method provided by the present invention, the facial emotion and heart rate of a target can be accurately detected, and music can be played intelligently according to a real-time psychological change of the user, so as to provide the best experience for the user.

The invention discloses a synthetic video generation method based on three-dimensional face reconstruction and video key frame optimization. The synthetic video generation method comprises the following steps: optimizing and fitting each parameter of a three-dimensional face deformation model for an input face image by adopting a convolutional neural network; training a voice-to-expression and head posture mapping network by using the parameters of the target video and the face model, and acquiring facial expression and head posture parameters from the input audio by using the trained voice-to-expression and head posture mapping network; synthesizing a human face and rendering the synthesized human face to generate a vivid human face video frame; training a rendering network based on a generative adversarial network by using the parameterized face image and the face image in the video frame, wherein the rendering network is used for generating a background for each frame of face image; and performing face background rendering and video synthesis based on video key frame optimization. The background transition of each frame of the output synthesized face video is natural and vivid, and the usability and practicability of the synthesized face video can be greatly enhanced.

Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face. The trained autoencoder is used to generate an output where the likeness of the face in the destination images is swapped with the likeness of the source face, while preserving expressions of the destination face.

Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face. The trained autoencoder is used to generate an output where the likeness of the face in the destination images is swapped with the likeness of the source face, while preserving expressions of the destination face.

A method of transferring a facial expression from a subject to a computer generated character that includes receiving a plate with an image of the subject's facial expression, a three-dimensional parameterized deformable model of the subject's face where different facial expressions of the subject can be obtained by varying values of the model parameters, a model of a camera rig used to capture the plate, and a virtual lighting model that estimates lighting conditions when the image on the plate was captured. The method can solve for the facial expression in the plate by executing a deformation solver to solve for at least some parameters of the deformable model with a differentiable renderer and shape from shading techniques, using, as inputs, the three-dimensional parameterized deformable model, the model of the camera rig and the virtual lighting model over a series of iterations to infer geometry of the facial expression and generate a final facial mesh using the set of parameter values of the deformable model which result in a facial expression that closely matches the expression of the subject in the plate.

A method is presented to address quantitative assessment of facial emotion nulling of a subject, where the method comprises the steps of: (1) presenting at least one scene, comprising a single facial expressions and a background, to a subject on a display; (2) adjusting the facial expression on the scene; (3) receiving feedback from the subject via at least one input device; (4) quantitatively refining the received feedback; (5) modulating the adjusted facial expression relative to the accuracy of the quantitatively refined feedback; (6) transforming the modulated facial expression; (7) calculating a critical threshold parameter; and (8) recording a critical threshold parameter onto a tangible computer readable medium. An apparatus for quantitative assessment of facial emotion nulling of a subject comprising a display device, an input device, a control device, and a tangible computer readable medium. In its simplest sense, a quantitative assessment profile of facial emotion nulling by psychophysical responses is generated on a tangible computer readable medium.

Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face. The trained autoencoder is used to generate an output where the likeness of the face in the destination images is swapped with the likeness of the source face, while preserving expressions of the destination face.

The invention discloses a fine-grained visualization system and method for emotional electroencephalography (EEG), and solves the technical problem of how to display fine-grained information in the emotional EEG. The system is connected with a data acquisition module, a data preprocessing module, a feature extraction module and a network training control module in sequence; an expression atlas provides a target image; the network training control module and an affective computing generative adversarial network (AC-GAN) module complete the training of an AC-GAN; a network forward execution module controls to complete the generation of fine-grained expressions. The method comprises the steps of collecting emotional EEG data, preprocessing the EEG data, extracting EEG features, constructing the AC-GAN, preparing the expression atlas, training the AC-GAN, and obtaining a fine-grained facial expression generation result. The emotional EEG is directly visualized into facial expressions withthe fine-grained information which can be directly recognized, and the visualization system is used for interactive enhancement and experience optimization of rehabilitation equipment, emotional robots, VR devices and the like with a brain-computer interface.

The invention provides a customer satisfaction analysis method based on video face expressions. The method comprises the following steps of acquiring customer video data; using an expression method with a base portion to modeling a face shape and an appearance; distinguishing fitting, updating incremental expressions, and carrying out parallel fitting and fitting evaluation; and according to a fitting evaluation result, analyzing customer satisfaction. In the invention, a sample scope is wide, a customer does not need to subjectively evaluate and grade so that man-made subjective factors are eliminated and the data is objective; and simultaneously, a lot of questionnaire data is avoided and manual labor is reduced, and efficiency and accuracy are increased.