Abstract: One variation of a method for predicting manufacturing defects includes: accessing a first set of inspection images of a first set of assembly units recorded by an optical inspection station over a first period of time; generating a first set of vectors representing features extracted from the first set of inspection images; grouping neighboring vectors in a multi-dimensional feature space into a set of vector groups; accessing a second inspection image of a second assembly recorded by the optical inspection station at a second time succeeding the first period of time; detecting a second set of features in the second inspection image; generating a second vector representing the second set of features in the multi-dimensional feature space; and, in response to the second vector deviating from the set of vector groups by more than a threshold difference, flagging the second assembly unit.

Abstract: An auxiliary diagnosis method for Parkinson's disease (PD) based on static and dynamic features of facial expressions is provided. Video data of various facial expressions performed by a to-be-tested patient is acquired and pre-processed to extract a plurality of optimal facial expression images corresponding to the various facial expressions. A similarity discrimination is performed on a synthesized happy facial expression image of the to-be-tested patient in a healthy state and an extracted happy facial expression image to obtain similarity features. Distances between multiple facial key points in the various facial expression images are calculated to obtain multiple key features, which are spliced with the plurality of key features to form static features. Coordinate change degrees of multiple facial key points of eyelids and mouth are calculated to obtain dynamic features. A classification prediction result of PD is output based on the spliced features.

Abstract: An image processing apparatus processes a kinetic image obtained by kymography of irradiating a subject with radiation to photograph a moving state of the subject. The image processing apparatus includes an acquisition unit, a generator, and an output controller. The acquisition unit acquires a plurality of frame images constituting the kinetic image. The generator generates a first image which is a synthesized still image obtained by synthesizing at least two or more frame images among the plurality of frame images. The output controller that outputs the first image to an output unit. Before generating the first image, the output controller outputs a second image which is a still image based on at least one or more frame images among the plurality of frame images and has an image quality lower than an image quality of the first image.

Abstract: In a sensing device that retains a code indicating access destinations, a data amount of the code is reduced. In a pixel array unit, a plurality of areas each include a predetermined number of pixels are arrayed. A reference access code retention unit retains a reference access code for designating, as access destinations, some of the pixels in a specific area among the plurality of areas. Anon-reference access code generation unit generates a non-reference access code for designating, as access destinations, the pixels in an area which does not correspond to the specific areas among the plurality of areas from the reference access code. A signal processing unit generates pixel data of pixels designated with the reference access code and the non-reference access code.

Abstract: A non-transitory, processor-readable medium stores instructions that, when executed by a processor, cause the processor to generate, using a first compute device, a video file. The non-transitory, processor-readable medium also stores instructions that, when executed by a processor, cause the processor to cause the video file to be sent to a second compute device that is cloud based, to cause the second compute device to: encode the video file, using a set of at least one software container, to generate an encoded video file; execute, at the set of at least one software container, a streaming protocol to generate a stream based on the encoded video file; and cause, via the set of at least one software container, generation of a set of analytics associated with the video file, based on the stream and using a virtualized software application environment.

Abstract: An electronic device and method for face detection based on facial key-points is provided. The electronic device receives an image of an object of interest. The image may include a face of the object of interest. The electronic device detects a plurality of key-points associated with the face of the object of interest based on the received image and determines a first coordinate value in the received image based on the detected plurality of key-points. Thereafter, the electronic device determines a region in the received image that includes the face of the object of interest based on the determined first coordinate value and controls the display device to overlay a marker onto the determined region of the face. The marker indicates a location of the determined region in the image.

Abstract: The present application relates to an information processing device and method, and a computer readable storage medium. The information processing device comprises a processing circuit, configured to generate a composite noise image on the basis of an input original image, process the black level in the composite noise image, and train, on the basis of the processed composite noise image, a machine learning model used for image denoising, to obtain a trained machine learning model.

Abstract: Disclosed herein is a method for face authentication. The method includes the following steps: a) at least one face detection step including determining at least one first image by using at least one camera; b) at least one skin detection step including projecting at least one illumination pattern including a plurality of illumination features on the scene by using at least one illumination unit, determining at least one second image using the at least one camera, and determining a first beam profile information; c) at least one 3D detection step including determining a second beam profile information of at least four of the reflection features located inside the image region of the second image corresponding to the image region of the first image; and d) at least one authentication step including authenticating the detected face by using at least one authentication unit.

Abstract: A method, system, and article is directed to real-time super-resolution image processing using neural networks.

Abstract: The present invention relates to the technical field of expression recognition, and in particular, to an expression recognition method and system based on multi-scale features and spatial attention. The method includes: performing feature extraction on acquired facial image data by using an HNFER neural network model to obtain an original input feature map; performing pooling and concatenation on extracted features based on a CoordAtt attention mechanism to obtain a feature map; performing deep convolution processing on the feature map to obtain an attention map, and then performing element-by-element multiplication to obtain a final feature map; and performing feature transformation and normalization on the final feature map to obtain an expression category probability and output the expression category probability.

Abstract: An electronic apparatus for image processing is disclosed.

Abstract: An eye gaze detection method includes: acquiring image data of a face of a person; detecting, from the image data, a left eye region including a left eye of the person and a right eye region including a right eye of the person; detecting, from the image data of the face, at least one of an ear region including an ear of the person and a hair region including hair of the person, when only one eye region of the right eye region or the left eye region is detected; detecting information indicating an orientation of the face based on information indicating a position of one eye included in the one eye region and information indicating the at least one; and detecting information indicating an eye gaze of the person based on the information indicating the position of the one eye and the information indicating the orientation of the face.

Abstract: Techniques are presented for detecting when drivers drive while drowsy. In some implementations, a drowsiness model is trained with data associated with inward videos and outward videos captured during a trip. The inward videos capture the inside of the cabin with the driver, and the outward videos capture the view in front of the vehicle in the direction of travel. Further, a device at the vehicle periodically calculates a drowsiness scale index value that indicates the level of drowsiness of the driver. Calculating the drowsiness scale index value includes obtaining a set of inward frames from the inward videos; for each inward frame, creating a face image by cropping the inward frame; obtaining a set of outward frames from the outward videos; calculating inward embeddings of the face images and outward embeddings of the outward frames; and calculating, by the drowsiness model, the drowsiness scale index value.

Abstract: A method for performing a screening includes illuminating a sample with light from a screen of a system at a first wavelength while the system is at a predetermined position with respect to the sample. The method also includes capturing a first image of the sample using a camera of the system while the system is at the predetermined position and the sample is illuminated with the light at the first wavelength. The method also includes illuminating the sample with the light from the screen at a second wavelength while the system is at the predetermined position. The method also includes capturing a second image of the sample using the camera while the system is at the predetermined position and the sample is illuminated with the light at the second wavelength. The method also includes combining the first and second images to produce a multispectral image.

Abstract: A method for identifying defects in a web of material translating along a travel path is provided. The method includes receiving a first image from a first camera; receiving a second image from a second camera; identifying a candidate as a possible defect within the first image; determining a first x-y position of the candidate relative to the first image; identifying the candidate within the second image; and determining the candidate is a probable defect based on the first x-y position and a second x-y position of the candidate within the second image. The first x-y position and the second x-y position predict the candidate is located on the web of material within a margin-of-error.

Abstract: A facial feature matching system comprises a facial feature matching engine. A first user selection of reference facial images is received, and facial features of reference faces are characterized using the facial feature recognition engine comprising a neural network with input, hidden, and output layers. The facial features are weighted. The weighted facial features are used to identify users that have facial features similar to the weighted facial features, wherein the respective reference faces include faces different than the faces of the users. Similarity indicators are generated for the identified users. The generated respective similarity indicators are used to generate a ordering of the identified users which is rendered via the user device. A first user selection of a second user in the ordered identified users is received and the first user and the second user are enabled to communicate over an electronic communication channel.

Abstract: A method for face authentication is proposed. The method includes at least one face detection step including determining at least one first image by using at least one camera, determining at least one material property from a second image, where the second image is recorded while projecting at least one illumination pattern including a plurality of illumination features on the scene, and at least one authentication step including authenticating the detected face by using the face detection and the material property.

Abstract: An exemplary method for detecting deepfake images and providing customized analysis comprises: receiving, from a user, a textual user inquiry regarding an image; inputting the textual inquiry and the image into a deepfake detection model, wherein the deepfake detection model comprises: an image encoder for generating a plurality of image embeddings based on the image; a text encoder for generating a plurality of textual embeddings based on the textual inquiry; one or more layers for generating a plurality of answer embeddings; and a language model for generating a textual analysis based on the plurality of answer embeddings; and outputting the textual analysis, wherein the textual analysis includes a classification result of whether the image is fake and further includes one or more visual features in the image and one or more attributes of the one or more visual features that contribute to the classification result.

Abstract: Systems and methods for replacement of scene, pose, and environment in videos and images using generative AI are provided. An example method includes receiving a first image of a face of a person, a second image of a body adopting a pose, and a text including a description of an environment of a scene; encoding the first image into an image embedding; extracting, from the second image, information concerning the pose of the body; encoding the text into a text embedding; randomly generating a noise for the image embedding; combining the noise and the image embedding to obtain a noisy image embedding; providing the noisy image embedding, the text embedding, and the information concerning the pose to a neural network to obtain a second noise; removing the second noise from the noisy image embedding to obtain a denoised image embedding; and decoding the denoised image embedding into an output image.

Abstract: Provided herein is an apparatus for assessing a color characteristic of a gemstone. The apparatus comprises an optically opaque platform for supporting a sample gemstone to be assessed, a daylight-approximating light source to provide uniform illumination to the gemstone, an image capturing component, and a telecentric lens positioned to provide an image of the illuminated gemstone to the image capturing component. Also provided are methods of color analysis based on images collected using such an apparatus.