48 results about "Face muscles" patented technology

The invention discloses a real-time training method for an expression database. The method comprises the following steps: S1, inputting in advance: enabling an actor to input expression coordinate sequences of all expressions of the expression database in advance before performance; S2, presetting a range: obtaining a preset range through big data analysis of values of the multidirectional tensionsensors corresponding to all facial feature point positions of each expression; S3, carrying out expression real-time acquisition: when an actor performs, making different expressions, and generatinga set of expression coordinate sequence consistent with the positions of the facial feature points in step S1; S4, comparing and screening: comparing and screening the numerical values of the multidirectional tension sensors corresponding to the positions of the facial feature points of the expression coordinate sequence; and S5, performing multi-sample training: continuously and accurately determining a predetermined range of the facial feature points through a large number of expression coordinate sequences. The motion state of the facial muscles is captured in real time in the performanceprocess, so that the preset range of each muscle of each expression of a specific actor is continuously updated and accurately determined, and the purpose of training a database is achieved.

The invention discloses a face recognition method based on fusion of dynamic and static features, especially a face recognition method based on comprehensive static features and dynamic features; static features focus on global contours, and face image features are regarded as high-dimensional features, through Linear and nonlinear transformations are mapped to low-dimensional subspaces, so that the features of the original sample are obtained in the low-dimensional space for classification. Dynamic features focus on local changes, mainly based on facial expressions, such as smiles, depression, etc., by extracting The dynamic features of facial muscle changes can obtain a set of feature functions of muscle changes and time, so as to perform accurate identification and classification, and improve the accuracy of face recognition.

The invention relates to a silent information recognition system based on facial muscle sound signals, comprising: a sensor for collecting facial movement signals; a signal conditioning circuit connected to the sensor to perform voltage stabilization and voltage scaling processing on the signals collected by the sensor; a single-chip microcomputer, Connect with the signal conditioning circuit, receive the signal processed by the signal conditioning circuit, and perform signal preprocessing, feature extraction processing and action classification processing on the signal in sequence, and output the classification result; Action classification results and display. Compared with the prior art, the present invention has the advantages of simple structure, good convenience, real-time and accurate transmission of silent signals, and the like.

The invention discloses a method for automatically marking facial muscle feature points, which is applied to a facial image analysis device and comprises the following steps of: collecting a to-be-recognized image containing the face of a user; executing a face recognition program on the to-be-recognized image to obtain a plurality of strong reference points on the face; performing fuzzy comparison on the to-be-recognized image based on a pre-trained training model and generating an recognition result; marking a plurality of muscle feature points on the to-be-recognized image according to the recognition result, wherein the plurality of muscle feature points respectively fall on a plurality of weak reference points on the face; and displaying the to-be-recognized image and the plurality of muscle feature points in an overlapping manner through a display unit. According to the invention, a plurality of muscle feature points for representing the facial muscle state can be automatically marked on the facial image of the user.

The present invention proposes a method, device, storage medium and terminal equipment for facial symmetry recognition, wherein the method includes: acquiring a facial image to be recognized; generating a surface texture image and a muscle texture image according to the acquired facial image ; According to the surface texture image, determine the facial contour symmetry of the facial image; according to the muscle texture image, determine the facial muscle symmetry of the facial image; and according to the facial contour symmetry and the facial muscle symmetry, generating suggestions for adjusting the symmetry of the face. With the present invention, the symmetry of the face can be recognized.