Systems and methods employing unique optics, combined with data gathering techniques that capture user interaction in the system at the point of engagement and point of entry. This facilitates gathering real time data on users, customers or other people during engagement with elements of the system to provide analytics in real time.

Aspects of the disclosure can provide method for identifying a face where multiple images to be identified are received. Each of the multiple images includes a face image part. Each face image of face images in the multiple images to be identified is extracted. An initial figure identification result of identifying a figure in the each face image is determined by matching a face in the each face image respectively to a face in a target image in an image identification library. The face images are grouped. A target figure identification result for each face image in each group is determined according to the initial figure identification result for the each face image in the each group.

In an example implementation according to aspects of the present disclosure, a system, method, and storage medium for processing digital image file metadata characteristics. The system includes a processor and memory. The processor executes machine readable instructions to receive a set of digital image files from a first client application. The processor extracts a set of metadata from the set of digital image files. The processor identifies a set of common characteristics within the set of metadata. The processor groups the set of digital image files based on the set of common characteristics. The processor evaluates an association between the set of common characteristics and a second user. Responsive to the evaluation, the processor sends the grouped set of digital image files to a second client application.

Systems and methods employing unique optics, combined with data gathering techniques that capture user interaction in the system at the point of engagement and point of entry. This facilitates gathering real time data on users, customers or other people during engagement with elements of the system to provide analytics in real time.

A presentation control device is provided for guiding a visitor in a specific area to an appropriate point in the area. The presentation control device (100) includes an acquisition unit (130) that acquires a photographed image photographed by a predetermined photographing device, an authentication control unit (140) that extracts a face area or facial feature information from the photographed image and causes an authentication device (200) to perform face authentication, a specification unit (160) that specifies presentation information to be presented for guiding to a predetermined point, based on a movement history and an action history being associated with a user ID of a user who succeeds in the face authentication, and an output unit (170) that transmits the presentation information specified by the specifying unit (160) to a predetermined display terminal.

An apparatus can include a memory, a communication interface, and a processor. The processor is configured to receive image data from an imaging device and first contextual data associated with the image data. The image data includes at least one image of a field of view. The processor is also configured to receive second contextual data associated with a user of a user device. The second contextual data is generated in response to the user device receiving a wireless signal sent by an antenna operably coupled to the imaging device. The processor is further configured to determine a potential presence of the user in the image data based on comparing the first contextual data with the second contextual data, analyze the image data to identify the user in the image data, and send the image data to the user.

Example implementations are directed to methods and systems for individualized multimedia navigation and control including receiving metadata for a piece of digital content, where the metadata comprises a primary image and text that is used to describes the digital content; analyzing the primary image to detect one or more objects; selecting one or more secondary images corresponding to each detected object; and generating a data structure for the digital content comprising the one or more secondary images, where the digital content is described by a preferred secondary image.

Embodiments of the present disclosure provide improved user identity validation. Embodiments of the present disclosure provide accurate and secure user identity validation in contexts where existing user validation algorithm(s), for example facial recognition algorithms, fail due to obfuscation of user physical characteristic(s) by clothing, equipment such as PPE masks, and the like. Some example embodiments receive captured data associated with a user, the captured data comprising at least imaging data associated with the user, detect, from the imaging data, machine decodable data associated with the user, determine an asserted user identity associated with the user by decoding the machine decodable data, and validate the asserted user identity associated with the user utilizing at least a remaining portion the captured data.

Computer implemented methods and devices for determining dimensions or distances of head features are provided. The method includes identifying a plurality of features in an image of a head of a person. A real dimension of at least one target feature of the plurality of features or a real distance between at least one target feature of the plurality features and a camera device used for capturing the image is estimated based on probability distributions for real dimensions of at least one feature of the plurality of features and a pixel dimension of the at least one feature of the plurality of features.

A method for facial recognition encode analysis comprises providing a training set of Gabor encoded arrays of face images from a database; and, for each encode array in the training set, evaluating the Gabor data to determine the accuracy of the fiducial points on which the encode array is based. The method also comprises training an outlier detection algorithm based on the evaluation of the encode arrays to obtain a decision function for a strength of accuracy of fiducial points in the encode arrays; and outputting the decision function for application to an encode array to be tested.