8 results about "Eigenface" patented technology

The invention discloses a medical image data management method and system based on artificial intelligence, and relates to the technical field of data management, and the method comprises the steps: collecting medical image data, converting the medical image data into an initial five-dimensional tensor, carrying out the preprocessing through a pulse neural network, and outputting a spatial-temporal characteristic spectrum; performing spatio-temporal joint feature face analysis on the spatio-temporal feature map by adopting an incremental feature space updating algorithm, extracting cross-slice features in combination with a three-dimensional convolution kernel, and generating a dimensionality reduction feature vector sequence; inputting the desensitization feature vector into a parallel detection network to generate a credibility scoring report; and triggering federal learning according to the credibility scoring report, dynamically updating the feature space parameters, and synchronizing the feature space parameters to the edge node through a secure communication protocol. Through high-dimensional tensor pulse coding and spatio-temporal joint feature analysis, the calculation efficiency and feature representation precision of the multi-modal medical image are improved.

The present invention discloses an artificial intelligence visual detection method based on a feature face method, which relates to the field of artificial intelligence technology, including synchronously collecting image data of visible light images, infrared images and depth images of the target object's face, and performing data preprocessing to form a multimodal facial feature standard data set; dynamically adjusting the weights in the feature vectors of each modality according to the current time, geographic location information and historical data statistics to form a comprehensive feature vector; using the comprehensive feature vector, identifying the identity of the target object through a machine learning classifier; when the recognition result reaches a preset confidence threshold, outputting the recognition conclusion, otherwise it will return to the feature extraction step. The present invention realizes adaptive optimization of the recognition strategy by integrating the feature face method of visible light, infrared and depth images, combined with a dynamic weight adjustment strategy, and effectively solves the problems of accuracy and robustness of face recognition in complex environments.

The present invention belongs to the field of information security technology and discloses a biometric key verification method based on zero-knowledge proof, which includes the following steps: Step 1: System initialization: In the system initialization stage, the key generation center randomly selects a local face database and uses the eigenface algorithm to calculate the eigenface template of the local face database; Step 2: Construct an encryption system; Step 3: Calculate and send identity information; Step 4: Generate keys and verification parameters; Step 5: Generate and send challenge values; Step 6: Calculate challenge value parameters; Step 7: Parameter verification and decryption of biometric keys. The present invention uses interactive zero-knowledge proof technology, which can not only satisfy the user's verification of the authenticity of the key generated by the key generation center based on biometric images, but also protect the user's privacy information.

The application relates to the field of IT applications and provides a face image generation method and device with face attributes and application thereof. The method comprises the following steps: obtaining a target face attribute image and a face image to be edited; inputting the target face attribute image and the face image to be edited into a face image generation network to obtain a target face image generated by the face image generation network; the face image generation network is used for generating the target face image based on the target face attribute image and the face image to be edited; wherein the face image generation network is trained based on a face sample image set, a feature face sample image set and a sample face attribute image extracted from the feature face sample image set. The method provided in the application can solve the technical problem that the appearance form of the face attribute on the generated face image is uncontrollable, and the generation efficiency of the face image with the face attribute is improved.

Embodiments of the present application relate to the technical field of computer vision, and provide a face image processing method and device and a storage medium, the method comprising: obtaining candidate face feature coefficients of a first user; obtaining a candidate face shape and a candidate face texture according to the candidate face feature coefficients, a preset eigenface, an average face shape and an average face texture vector; generating a candidate adversarial patch based on the candidate face shape and the candidate face texture; obtaining a candidate adversarial sample, the candidate adversarial sample being obtained by superimposing the candidate adversarial patch and an attacker face image of a second user; obtaining a similarity between the candidate adversarial sample and a target face image; if the similarity is less than a preset value, updating the candidate feature coefficients and the candidate adversarial patch until the similarity is greater than the preset value, and outputting the candidate adversarial patch at this time as a target adversarial patch. The present scheme can improve the adversarial property of the adversarial patch and avoid reducing the attack effect due to deformation or face fitting degree.

The invention discloses a face animation generation method and device and a storage medium, and relates to the technical field of digital humans, and the face animation generation method comprises the steps: coding an input audio based on a whisper model and a wav2cev model, and obtaining an audio feature vector; public features, face features, head posture features and lip features are extracted based on the input face image, and the public features comprise face grid features, tooth features and eye features; the first combined feature and the second combined feature are fused to obtain a fused feature, the first combined feature comprises a common feature, a face feature and a head posture feature, and the second combined feature comprises a common feature and a lip feature; and taking the fusion feature and the audio feature vector as condition information, and injecting the condition information into a diffusion model through a cross attention mechanism, so that the diffusion model generates a face animation, and accurate synchronization of the audio information and the face action in the face animation is realized.

The invention provides an image recognition method and device based on NMF and PCA and a medium, and relates to the technical field of computer vision and information security, and the method comprises the steps: converting an obtained target image into frequency domain representation, and unfolding the target image of the frequency domain representation into a target image frequency domain vector, using PCA to map the frequency domain vector of the target image based on the eigenface matrix to obtain a first eigenvector of the target image, using NMF to map the frequency domain vector of the target image based on the basis matrix to obtain a second eigenvector of the target image, and using a plurality of convolution layers to perform feature fusion on the combined eigenvector of the target image to obtain a second eigenvector of the target image; the method comprises the steps of obtaining a target image fusion feature vector, adding noise to the target image fusion feature vector by using a differential privacy method, obtaining a target image transmission vector, uploading the target image transmission vector to a target server for image recognition, and obtaining a recognition result of the target image, so that the recognition result of the target image is more accurate.

The present application relates to face recognition technology, in particular to a face database building and updating method and device based on mobile terminal and a storage medium, the method comprising: uploading dynamic video and face photos of the face through the mobile terminal; extracting three-dimensional geometric features of the face through the dynamic video, generating corresponding three-dimensional feature faces according to the three-dimensional geometric features and the reference photos, and storing the three-dimensional feature faces into the face database; simulating the three-dimensional feature faces according to the light intensity, angle, shielding state, skin color and age information of the reference photos, comparing the similarity of the reference photos and the simulated three-dimensional feature faces; and replacing the three-dimensional feature faces stored in the face database through the judgment of the first similarity threshold and the second similarity threshold. The present application reduces the difficulty of collecting the face database and improves the accuracy and comprehensiveness of face recognition.