Abstract: The present disclosure is directed to a system and method of controlling a facial recognition process by validating preconditions with a ranging sensor. The ranging sensor transmits a ranging signal that is reflected off of a user's face and received back at the ranging sensor. The received ranging signal can be used to determine distance between the user's face and the mobile device or to determine the reflectivity of the user's face. Comparing the distance to a range of distances corresponding to normal operation of the device or normal reflectivities associated with human skin tones can reduce the number of false positive activations of the facial recognition process. Furthermore, a multiple zone ranging sensor can produce a face depth map that can be compared to a stored face depth map or can produce a reflectivity map that can be compared to a stored face reflectivity map to further increase power efficiency and device security.

Abstract: The embodiment of the present application provides a method, apparatus and application system for extracting a target feature. The method includes: acquiring target area video data captured by a panoramic camera; determining, by a target detection algorithm, a tracking target having a preset feature in the target area video data; allocating the tracking target to a detail camera, such that the detail camera tracks the tracking target and acquires close-up video data of the tracking target; extracting, from the close-up video data, attribute information of the tracking target. With the embodiment of the present application, attribute information of each target can be accurately extracted, improving the accuracy of extracting the attribute information of the target.

Abstract: Disclosed are systems and methods for providing personalized videos. An example method includes storing one or more preprocessed videos. The one or more preprocessed videos may include at least one frame with at least a target face. The method may continue with receiving an image of a source face, for example, by receiving a user selection of a further image and segmenting the further image into portions including the source face and a background. The method may then proceed with modifying the one or more preprocessed videos to generate one or more personalized videos. The modification may include modifying the image of the source face to generate an image of a modified source face. The modified source face may adopt a facial expression of the target face. The modification may further include replacing the at least one target face with the image of the modified source face.

Abstract: There is provided a main subject determining apparatus. A subject detecting unit detects a plurality of subjects from a first image. An obtaining unit obtains posture information of each of the plurality of subjects. For each of the plurality of subjects, a calculating unit calculates, on the basis of the posture information of the subject, a reliability corresponding to a likelihood that the subject is a main subject in the first image. A determining unit determines the main subject of the first image from among the plurality of subjects on the basis of the plurality of reliabilities calculated for the plurality of subjects.

Abstract: A user terminal includes: a communication interface configured to receive an image of a surveillance area, and transmit a control command to a first object; a display configured to display the image and a control tool regarding the first object; a user interface configured to receive a first user input to select the first object displayed in the image, and a second user input to control an operation of the first object; and a processor configured to: determine whether a user has a right to control the first object in response to the first user input; and based on determining that the user has the right to control the first object, display the control tool on the display, and generate the control command according to the second user input.

Abstract: A control apparatus includes one or more processors which functions as a detection unit configured to acquire image data captured by an image pickup unit and detect an object from the image data, a capturing control unit configured to output an instruction to start capturing to the image pickup unit to cause the image pickup unit to automatically capture moving images, a camerawork decision unit configured to decide camerawork to be given to the moving images based on information indicating a detection result from the detection unit, and a control unit configured to perform control to change at least one of a composition of the image pickup unit and a focus of the photographic optical system with a predetermined pattern during the capturing of the moving images based on a decision result from the camerawork decision unit.

Abstract: A system, method, and device for generating Pepper's Ghost artifices from two-dimensional sources including Augmented Reality (“AR”) or Virtual Reality (“VR”) environments such that the Pepper's Ghost artifices appear to be a natural addition to a three-dimensional virtual environment. By employing virtual Pepper's Ghost projections onto varying size and shaped screens in the virtual three-dimensional environment, a reduction in bandwidth and costs are realized particularly when displaying humanoid characters in an AR and/or VR environment. While the methods disclosed with the present invention could be of utility to any type of virtual environment, the benefits are particularly acute for dynamic VR environments.

Abstract: A system for customizing soundtracks and hairstyles in modifiable videos is provided. In one example embodiment, the system includes a memory storing processor-executable codes and a processor configured to receive a modifiable video and a user image including a facial image and a hair image; analyze the facial image and the hair image to determine at least one hair property, determine whether the hair image is modifiable, and determine modifications to the at least one hair property; modify the at least one hair property to generate a modified hair image; generate a further image including the modified hair image and the facial image; and generate, based on the further image and the modifiable video, a personalized video that includes at least a part of the further image and at least a part of the modifiable video.

Abstract: An image processing apparatus includes a first processor configured to obtain, from a color image, an illumination element image and an albedo element image corresponding to the color image, and a second processor configured to divide the illumination element image into a plurality of subelement images each corresponding to the color image.

Abstract: A method for adding a virtual item can include: acquiring classification identifiers of a plurality of pixel points in a target human face image, wherein the classification identifier comprises a first identifier of pixel points in a first human face part or a second identifier of pixel points in a second human face part; determining a target region in the target human face image based on the classification identifiers, wherein the target region is a region belonging to the first human face part; adding a virtual item to the target region; wherein the first human face part comprises an uncovered human face part, and the second human face part comprises a covered human face part or a non-human face part.

Abstract: Embodiments herein disclose systems, methods, and computer-readable media for integrating facial recognition technology into clinical workflows. An application can manage receipt of a source image, including a face of an unidentified individual, and communicate the source image for facial recognition processing. The facial recognition processing can identify an individual and demographic information associated thereto, as well as provide information to access an electronic health record server housing one or more electronic health records. The application can access health-related data for the individual from the individual's EHR and rank the accessed information to communicate to a source device in a custom, prioritized communication.

Abstract: A system, device, and a method for guiding a user to comply with one or more application-specific requirements by using sequentially two or more neural networks run on one more video frame of a scene to detect at least one requirement of the one or more application-specific requirements. Upon the detection result, the application guides a user to adjust the scene based on the detection until the scene is adjusted to meet the application-specific requirements.

Abstract: A computing device generates a user interface that includes a viewing window and a toolbar including a selection tool. The computing device displays a live video depicting one or more individuals in the viewing window of the user interface and generates a segmentation mask for each individual depicted in the live video, where each segmentation mask comprises facial feature vectors of a facial region of each individual. The computing device obtains selection of an individual depicted in the live video and compares facial feature vectors of each of the individuals depicted in the live video with the facial feature vector of the selected individual. The computing device converts the segmentation masks of individuals with corresponding facial feature vectors that do not match the selected facial feature vector to a filter mask and composites the filter mask with a background content of the live video.

Abstract: Examples described herein generally relate to processing a first image captured by the first camera at a first time to determine a first set of multiple key points of a face, processing a second image captured by the second camera at a second time to determine a second set of the multiple key points on the face in the second image, determining a location of at least a portion of the multiple key points in a three-dimensional space based on a first location of each of the portion of the multiple key points in the first image and a second location of each of the portion of the multiple key points in the second image, and detecting whether the face is a valid three-dimensional face for facial recognition based at least in part on the location of at least the portion of the multiple key points in the three-dimensional space.

Abstract: An ATM device may receive a request to process an ATM transaction; dispense, via an instrument dispenser, a plurality of instruments based on the request; perform image segmentation of one or more images of an area surrounding the instrument dispenser, wherein the image segmentation is performed using a deep learning network trained using synthetic models of hands; detect, based on performing the image segmentation, that a user's hand approaches the instrument dispenser after dispensing the plurality of instruments; determine, after dispensing the plurality of instruments and after detecting that the user's hand approaches the instrument dispenser, that a portion of the plurality of instruments is present at the instrument dispenser; and perform one or more actions based on determining that the portion of the plurality of instruments is present at the instrument dispenser.

Abstract: A method of tracking an object across a stream of images comprises determining a region of interest (ROI) bounding the object in an initial frame of an image stream. A HOG map is provided for the ROI by: dividing the ROI into an array of M×N cells, each cell comprising a plurality of image pixels; and determining a HOG for each of the cells. The HOG map is stored as indicative of the features of the object. Subsequent frames are acquired from the stream of images. The frames are scanned ROI by ROI to identify a candidate ROI having a HOG map best matching the stored HOG map features. If the match meets a threshold, the stored HOG map indicative of the features of the object is updated according to the HOG map for the best matching candidate ROI.

Abstract: A system comprises a picture and metadata captured by a content capture system; a recognizable characteristic datastore configured to store recognizable characteristics of different users; a module configured to identify a time and a location associated with the picture based on the metadata, and to identify one or more potential target systems within a predetermined range of the location at the time; a characteristic recognition module configured to retrieve the recognizable characteristics of one or more potential users associated with the potential target systems, and evaluate whether the picture includes one or more representations of at least one actual target user from the potential users based on the recognizable characteristics of the potential users; a distortion module configured to distort a feature of the representations of the least one actual target user in response to the determination; a communication module configured to communicate the distorted picture to a computer network.

Abstract: An image processing apparatus includes memory that stores a plurality of images acquired by image-capturing a face of a person; and a processor, coupled to the memory, configured to: acquire a pixel value pattern indicating a relationship between positions in a given direction and pixel values in an area having parts of the face of each of the plurality of images, and select an image to be processed from the plurality of images based on the pixel value patterns of the plurality of images.

Abstract: A station device in a biometric pre-identification system uses identity to perform one or more actions. Identities are determined (such as via a backend) using biometric information. A biometric pre-identification device obtains biometric information and/or a digital representation thereof from a person approaching the station device. The biometric pre-identification device transmits such to the station device, facilitating the station to begin and/or perform various actions. The station device begins or performs the actions using the identity determined based on the biometric information before the person arrives at the station device.

Abstract: Single tap launch and login to a secure application is provided. User authentication information is verified based on fingerprint data in response to the data processing system receiving an input via a finger of a user on a display screen to execute the secure application. The user authentication information is passed to the secure application as an invoking parameter to execute the secure application. Content corresponding to the secure application is received in response to execution of the secure application.

Abstract: Embodiments of the present disclosure disclose an object detection method, an object detection apparatus, a related device, a storage medium and a vehicle. The method includes the following. Scene point cloud data is inputted into a point cloud feature extraction model pretrained to obtain a point cloud descriptive feature of the scene. Scene image data is input into an image feature extraction model pretrained to obtain an image descriptive feature of the scene. The point cloud descriptive feature and the image descriptive feature of each target region in the scene are input into an object identifying model to obtain a detection result of an object included in each target region.

Abstract: A method, device, system, and computer medium for providing interactive advertising are provided. For example, a device may request an advertisement from a remote server, receive the advertisement, receive a response from a user who is listening and/or watching the advertisement, and transmit the response to the server for further action. The user may input a response by speaking. A server may receive an advertisement request from the device, select an advertisement based on pre-defined one or more criteria, transmit the selected advertisement to the device for play, receive from the device a response to the selected advertisement, and then perform an action corresponding to the received response.

Abstract: The present invention is a method and system for evaluating relative effectiveness of content in a digital signage network, using a series of measurements to compare and evaluate different contents. The measurements are performed on a plurality of input images of the people captured by a plurality of means for capturing images in the vicinity of at least a digital signage. The present invention is a content rating system based on how the audience responds to the digital content in the intended context of digital media network in-store or in other public viewing areas. The present invention allows the measurement of the response to the content for different segments, further allowing for better planning of the content and optimizing the advertising dollars.

Abstract: A method and an apparatus for identity verification, an electronic device, a computer program, and a storage medium include: obtaining a first image of a document, where the first image contains a first face image; obtaining a second image containing a face of a to-be-verified person; performing face comparison on the first image and the second image to obtain a first comparison result; and obtaining an identity verification result according to the first comparison result.

Abstract: Techniques for cooperative document generation include methods, one of the methods includes receiving, from a mobile device, a request to start an insurance claim, the mobile device including an application configured to guide the user through the claim process. The method includes establishing a session between a computer and the mobile device. The method includes displaying images of the user interface of the mobile device. The method includes receiving information concerning the insurance claim from the mobile device, the information provided by the user in response to prompts provided on the mobile device. The method includes displaying the information on the computer. The method includes enabling the customer service representative to alter the information or request additional information be provided. The method includes adding the information to a data record regarding the insurance claim in response to an indication that the customer service representative has verified the information.

Abstract: A passenger state detection device (100) includes: a correction parameter setting unit (30) for setting a correction parameter for a captured image captured by a camera (2) for capturing a vehicle interior for each of detection items in passenger state detecting process including the multiple detection items using at least one of a feature amount in a face part area that corresponds to a passenger's face part in the captured image or a feature amount in a structure area that corresponds to a structure in the vehicle interior in the captured image; and an image correcting unit (40) for correcting the captured image for each of the detection items in the passenger state detecting process using the correction parameter set by the correction parameter setting unit (30).

Abstract: A method for sending early warning information, a storage medium and a terminal are provided. The method includes: calculating a target similarity between a first face image and a target face image when the first face image captured by an imaging device is acquired; and generating and sending early warning information corresponding to the first face image if the target similarity reaches a similarity threshold at the current moment; wherein, the similarity threshold is determined by a fluctuation degree value of a plurality of similarities in a similarity sample, the similarity in the similarity sample is a target similarity corresponding to a generated warning information, and the similarity sample is updated over. As a result, the accuracy in early warning may be improved.

Abstract: The present disclosure provides an age recognition method, a non-transitory computer-readable storage medium, and an electronic device. The method includes extracting feature points of a face in an image, preprocessing the image to extract global features of the face, extracting local features of the face based on the feature points, determining an age feature of the face according to the global features and the local features, and inputting the age feature into a pre-trained age recognition model to obtain an age value corresponding to the face in the image.

Abstract: The present technology relates to an imaging apparatus, an image processing apparatus, and an image processing method that can reduce an amount of transfer of images. The imaging apparatus includes: an imaging unit that performs imaging to obtain a captured image; and a transmission control unit that performs transmission control to transmit a region image within a plurality of transfer regions, which corresponds to an entire or partial region of the captured image, at a frame rate set for each of the transfer regions. The present technology can be applied to, for example, a camera that images the surroundings of a mobile body such as a camera that images the surroundings of a vehicle that performs automated driving.

Abstract: In one embodiment, a set of feature vectors can be derived from any biometric data, and then using a deep neural network (“DNN”) on those one-way homomorphic encryptions (i.e., each biometrics' feature vector) can determine matches or execute searches on encrypted data. Each biometrics' feature vector can then be stored and/or used in conjunction with respective classifications, for use in subsequent comparisons without fear of compromising the original biometric data. In various embodiments, the original biometric data is discarded responsive to generating the encrypted values. In another embodiment, the homomorphic encryption enables computations and comparisons on cypher text without decryption. This improves security over conventional approaches. Searching biometrics in the clear on any system, represents a significant security vulnerability. In various examples described herein, only the one-way encrypted biometric data is available on a given device.

Abstract: An information processing apparatus (100) includes an acquisition unit (122) that acquires a first image from which person region feature information regarding a region including other than a face of a retrieval target person is extracted, a second image in which a collation result with the person region feature information indicates a match, and a facial region is detected, and result information indicating a collation result between face information stored in a storage unit and face information extracted from the facial region, and a display processing unit (130) that displays at least two of the first image, the second image, and the result information on an identical screen.

Abstract: Comprehensive 2D learning images are collected for learning subjects. Standardized 2D gallery images of many gallery subjects are collected, one per gallery subject. A 2D query image of a query subject is collected, of arbitrary viewing aspect, illumination, etc. 3D learning models, 3D gallery models, and a 3D query model are determined from the learning, gallery, and query images. A transform is determined for the selected learning model and each gallery model that yields or approximates the query image. The transform is at least partly 3D, such as 3D illumination transfer or 3D orientation alignment. The transform is applied to each gallery model so that the transformed gallery models more closely resemble the query model. 2D transformed gallery images are produced from the transformed gallery models, and are compared against the 2D query image to identify whether the query subject is also any of the gallery subjects.

Abstract: A support for image processing is provided, comprising: (a) detecting respective face regions from images consecutively photographed for a first person at predetermined time intervals by an image pickup unit to display images of the face regions detected in relation to the first person in a first region of a screen, and providing a user interface for indicating that a specific face image is selected from the face images of the first person displayed in the first region; (b) additionally displaying the specific face image through a second region adjacent to the first region; and (c) displaying a synthesized image using the specific face image as a representative face of the first person, when the specific face image displayed through the second region is selected.

Abstract: The present disclosure provides a video blending method, apparatus, electronic device and readable storage medium, and relates to computer vision technologies.

Abstract: A wireless access system at a building is provided. A door lock system includes: a lock status device configured to be coupled to the drive shaft of a lock device, the lock status device assisting in locking and unlocking a lock of a lock device. A processor is coupled to the door lock system. An image capture device at the building is configured to be in communication with the door lock system and capture an image of an object in the vicinity of the building. A light source assembly is in communication with the image capture device.

Abstract: A system or method executing an intelligent appearance monitoring management system comprising a processor to execute code instructions of a multimedia multi-user collaboration application to join a videoconference session, a display screen, a speaker, a video camera, and a microphone where the video camera captures a videoframe of a user and the processor to input videoframe data, including the detected user's image, into a trained neural network of the intelligent appearance monitoring management system to generate optimized appearance filtering adjustments indicating detection of a user appearance anomaly in the user's image or altering a user's image in the captured videoframes in response to the user appearance anomaly and prepare those videoframes for transmission.

Abstract: A system and method for suspect identification, the computer implemented method including a digital catalogue for users to captured images of suspects whereby the captured images are then compared to existing images having identifying information to identify the suspect. The system also presents to a user “a no trespass” statement containing applicable laws prohibiting unlawful trespass that may be read to a suspect whereby the audio and video of the reading may be captured and stored in the system.

Abstract: The embodiments disclose an apparatus including an eyewear pupilometer for detecting, measuring and processing a wearer's pupil movement and size, for detecting and processing retinal images, for detecting and processing a wearer's field of view, for broadcasting alerts, for pre-diagnostic screening, for overriding vehicle operation and for measuring, recording and transmitting circadian responses, at least one eyewear pupilometer module including a lens fiber optic camera module, an image processor module, a retinal image infrared detector module, an outward camera module, at least one alert module, an alert light and message projector, a WI-FI module, an automated pullover module, an automated steering module, fiber optic & data cables, a contact lens pupilometer image, sensor and processor module, and at least one eyewear pupilometer module coupled to and/or embedded into eyewear frames and lenses, contact lenses, a vehicle wind shield and protective covers for hand held devices and laptop computers.

Abstract: A skin color identification method comprises: acquiring an image of human face; determining a target color gamut difference of respective pixels in the image of human face, the target color gamut difference of the respective pixels being a difference between intensity values of two designated color components of the respective pixels; and determining a confidence degree of skin color that the skin color of a human face in the image of human face belongs to a target skin color according to the target color gamut differences of all pixels in the image of human face, the confidence degree of skin color reflecting a probability that the skin color of the human face in the image of human face is the target skin color. A skin color identification apparatus and a computer-readable storage medium are further provided.

Abstract: A face image processing method and apparatus, an electronic device, and a storage medium are provided. The method includes: obtaining face key points and a face deflection angle in a face image; determining a submalar triangle center in the face image according to the face key points and the face deflection angle; determining a submalar triangle region in the face image according to the face key points and the submalar triangle center; and performing color filling on the submalar triangle region. By means of the present disclosure, a submalar triangle region can be accurately positioned, and submalar triangle filling is performed based on the accurately positioned submalar triangle region, thereby obtaining a more natural filling effect.

Abstract: An information processing apparatus includes an input, a blood-relative list generator, a similar image searcher, and a suspect information generator. The input receives DNA information of a suspect and facial image relating to a plurality of facial images. The blood-relative list generator generates a list of blood relatives who are presumed to be blood relatives of the suspect from a plurality of pieces of DNA information. The similar image searcher calculates degree of similarity between facial images of persons on the blood-relative list and each of the plurality of facial images, and searches for and retrieves a facial image resembling the image of the person on the blood-relative list based on the calculated degree of similarity. The suspect information generation part generates suspect information by associating information relating to the retrieved facial image with information relating to the person on the blood-relative list who resembles the retrieved facial image.

Abstract: An adaptive spoofing method includes: causing a first display device to display a spoof representation of a human user; and obtaining multiple images of the spoof representation. The multiple images are captured automatically by an image capture device, each of the multiple images captures a different corresponding configuration of the spoof representation displayed on the first display device. The method also includes: executing a biometric authentication process separately on each of at least a subset of the multiple images; determining that the biometric authentication process authenticates the human user based on at least a first image from the subset; and identifying a configuration of the spoof representation corresponding to the first image as a failure condition associated with the biometric authentication process.

Abstract: An apparatus includes a memory of a user device and a processor of the user device. The processor is configured to capture an image using an image capture device of the user devices and broadcast a request signal within a range of the user device. The request signal is a request for facial data from compute devices within the range. The processor is configured to receive, in response to the request signal, facial data from each compute device from a set of compute devices within the range and perform, using the facial data received from each compute device from the set of compute devices, facial recognition on the image to identify a match between the facial data from a subset of compute devices from the set of compute devices and facial data from the image. The processor is configured to transmit the image to the subset of compute devices.

Abstract: A method for automatic correction and generation of facial images includes storing, by a computer system, multiple constraints specifying an image quality. The computer system receives a first image of a face of a user from a computer device. The computer system determines that the first image of the face of the user violates at least one constraint of the multiple constraints specifying the image quality. Responsive to the determining that the first image of the face of the user violates the at least one constraint, the computer system generates a second image of the face of the user based on the first image of the face of the user and the at least one constraint, such that the second image of the face of the user satisfies the at least one constraint. A display device of the computer system displays the second image of the face of the user.

Abstract: A facial image identification system is provided to calculate a first feature amount related to each of features from first facial image data used in machine learning for constructing a first identifier that identifies the features of a face, calculate a second feature amount related to each feature from second facial image data obtained in the environment using the first identifier, and compare the first and the second feature amounts for each feature. The system extracts a feature having a large difference between the first and the second feature amounts as a difference feature, and constructs, by implementing machine learning that third facial image data is used, a second identifier for identifying the difference feature and/or a difference-related feature. The third facial image data is acquired in the environment that uses the first identifier and reflects the difference feature and/or the difference-related feature in the third facial image data.

Abstract: A method, computer program product, and a system where a processor(s) obtains a video from a user, via a client, and segments the video into temporal shots that comprise a timeline of the video. The processor(s) cognitively analyze the video, by applying an image recognition algorithm to identify image entities in each temporal shot of the video and by applying a data structure comprising a user profile of the user to the temporal shots, to identity personal entities in each temporal shot of the video. The program code generates a search index for the video, utilizing the user entities (image entities and personal entities), where each entry of the search index is a given user entity and a linkage to a given temporal shot and the linkage indicates a location of the given user entity in the timeline of the video.

Abstract: The present disclosure provides systems and methods that perform face reconstruction based on an image of a face. In particular, one example system of the present disclosure combines a machine-learned image recognition model with a face modeler that uses a morphable model of a human's facial appearance. The image recognition model can be a deep learning model that generates an embedding in response to receipt of an image (e.g., an uncontrolled image of a face). The example system can further include a small, lightweight, translation model structurally positioned between the image recognition model and the face modeler. The translation model can be a machine-learned model that is trained to receive the embedding generated by the image recognition model and, in response, output a plurality of facial modeling parameter values usable by the face modeler to generate a model of the face.

Abstract: A method includes determining information indicative of at least one facial characteristic associated with at least one face in the source image, processing the source image using a filter based on the determined information, performing wavelet decomposition on each of the filtered image and the source image, determining weightage factors associated with the wavelet decomposition of each of the filtered image and the source image, based on the determined information, obtaining a wavelet image to generate a texture restored image from the wavelet decomposition of each of the filtered image and the source image based on the weightage factors.

Abstract: A method for analyzing media to evaluate talent of a subject portrayed in the media is provided. The steps describe receiving a plurality of the media at a server, the media being performance based media; transforming the media into at least a data set corresponding to at least a characteristic of the media at the server, wherein the server is in communication with a node; identifying features in the data set that correspond to a probability of success of the subject in the media; receiving subjective opinion polling data from a plurality of participants as to whether the subject in the media has talent; training the node via machine learning algorithm to identify, using the identified features in the data set and the subjective opinion polling data provided, whether the subject is likely to have talent; and executing the machine learning algorithm to output a score relating to the talent of the subject in the media. A system for discovering talent is also provided herein.

Abstract: This application relates to a face recognition method performed at a computer server. After obtaining a to-be-recognized face image, the server inputs the to-be-recognized face image into a classification model. The server then obtains a recognition result of the to-be-recognized face image through the classification model. The classification model is obtained by inputting a training sample marked with class information into the classification model, outputting an output result of the training sample, calculating a loss of the classification model in a training process according to the output result, the class information and model parameters of the classification model, and performing back propagation optimization on the classification model according to the loss.