Systems, devices, media and methods are presented for generating biometric image data. In one example, a system accesses a set of images stored on a mobile computing device. The system identifies one or more faces depicted in the set of images and generates a set of face images from the set of images. The system determines a set of positions of a set of facial features depicted within the set of face images and generates a set of biometric reference maps based on the set of positions. The system transmits the set of face images to a reference server and stores the set of biometric reference maps on the mobile computing device.

A notification system notifies users when there is a match between images. The notification system includes a network interface receiving images from a plurality of user devices including a first user device and a second user device, a memory storing database and instructions, and a processor. The processor executes the instructions to function as an image processing unit processing the received images, a face recognition unit recognizing one or more faces in each received image, a face matching unit checking whether a face in a first image from the first user device matches a face in a second image from the second user device, a metadata processing unit processing metadata in each received image, and a notification unit notifying the first user device and the second user device in a case where the face in the first image matches the face in the second image.

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.

A system, device, and method for collecting user information. An image and metadata associated with the image are captured utilizing a wireless device. The image and the metadata are associated with a device. The image and the metadata are processed utilizing the wireless device to determine user information associated with the device. The user information is distributed from the wireless device to one or more devices associated with the user information.

A method for recognizing persons in video streams includes obtaining a live video stream, detecting a first person in the live video stream, determining from analysis of the live video stream first information that identifies an attribute of the first person, determining based on at least some of the first information that the first person is not identifiable to the computing system, storing at least some of the first information, receiving a user classification of the first person as being a stranger, and deleting the stored first information.

An information processing apparatus (100) includes a collation unit (102) that collates first feature information extracted from a person included in a first image (10) with first feature information indicating a feature of a retrieval target person, an extraction unit (104) that extracts second feature information from the person included in the first image in a case where a collation result in the collation unit (102) indicates a match, and a registration unit (106) that stores, in a second feature information storage unit (110), the second feature information extracted from the person included in the first image.

A training data system enables the generation of training data based on video content received from one or more outside video sources. For example, the generated training data can include a transcript of a word or phrase alongside emotion, language style, and brand perception data associated with that word or phrase. To generate the training data from a video, the subtitles, video frame, metadata, and audio levels of the video can be analyzed by the training data system. The generated training data (potentially from a plurality of videos) can then be grouped into a set of training data and used to train machine learning modules for Natural Language Processing (NLP) techniques.

The various implementations described herein include systems and methods for recognizing persons in video streams. In one aspect, a method includes: (1) obtaining a live video stream; (2) detecting person(s) in the stream; and (3) determining, from analysis of the live video stream, personally identifiable information of the detected person(s); (4) determining, based on the personally identifiable information, that the first person is not known to the computing system; (5) in accordance with the determination that the first person is not known: (a) storing the personally identifiable information; and (b) requesting a user to classify the first person; and (6) in accordance with (i) a determination that a predetermined amount of time has elapsed since the request was transmitted and a response was not received, or (ii) a determination that a response was received classifying the first person as a stranger, deleting the stored personally identifiable information.

A method, system and computer program product that provides virtual assistance in facilitating visual comparison is disclosed. A method in accordance with example embodiments includes determining (by comparison of first metadata of an at least one user-provided image to second metadata of an at least one reference image) difference information as between an unknown object and a known object shown in the at least one user-provided image to the at least one reference image respectively.

Systems and method verify a user based on facial image data, without prior information about the user. A user name and facial image of the user are received. A search query comprising the user name can be issued to one or more search engines. Images returned as a result of the search query can be filtered to determine a set of candidate images. The images in the set of candidate images can be compared to the facial image of the use to determine a probability of a match. If there is a match, the user can be considered verified.