Abstract: A method, apparatus and computer program utilize digital signatures to accurately and efficiently identify changes to objects of interest within captured images. In the context of a method, a digital signature is obtained for an object of interest at a particular location. The method also determines whether a difference between the digital signature and a previously determined digital signature associated with the location satisfies a predefined criterion. In accordance with determining that the difference fails to satisfy the predefined criterion, the method causes information regarding the object of interest at the particular location to be collected, such as to permit a map that references the object of interest or other information associated with the object of interest to be updated.

Abstract: Biometric input, such as an image of a hand, may be processed to determine embedding vector data that may be used to identify users. Accuracy of the identification is improved by using high resolution inputs to a deep convolutional neural network (DCNN) that is trained to generate the embedding vector data that is representative of features in the input. Training data sets are expensive to develop and thus may be relatively small. During training of the DCNN, confidence loss values corresponding to the entire input as well as particular patches or portions of the input are determined. These patch-wise confidence loss values mitigate potential overfitting during training of the DCNN and improve overall performance of the trained DCNN to determine embedding vector data suitable for identification.

Abstract: 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.

Abstract: This disclosure describes techniques for identifying users that are enrolled for use of a user-recognition system and updating identification data of these users over time. To enroll in the user-recognition system, the user may initially scan his or her palm. The resulting image data may later be used when the user requests to be identified by the system by again scanning his or her palm. However, because the characteristics of user palms may change over the time, the user-recognition system may periodically perform processes for updating the identification data stored in association with the user in order to maintain or increase an accuracy of the user-recognition system.

Abstract: A method for obtaining image data of a subject, including; a first scanning step including a plurality of steps W, each step W being a step of determining one place existing in a one-dimensional, two-dimensional, or three-dimensional first space; and a second scanning step of scanning insides of second spaces including at least one of the places, wherein the second scanning step includes a step X of randomly determining a location of an observation point and a step Y of obtaining a piece of image data for the observation point, and, at a time point of end of scanning an inside of one of the second spaces, the second space has a first region including 50% of observation points and a second region existing outside the first region and including remaining 50% of the observation points, the second region being larger than the first region by at least 15%.

Abstract: A method for an image processing circuit includes steps of: receiving a fingerprint image; performing a low-pass filtering on the fingerprint image to remove a moiré signal on the fingerprint image, to generate a filtered image; and performing a data binning on the filtered image to generate an output image.

Abstract: Video containers are expanded to encapsulate auxiliary data and metadata linking video content with relevant portions of auxiliary data for download during playback of particular video content. Auxiliary data is parsed into areas of interest and associated with the video content including the same areas of interest. During playback a viewer is provided access to relevant portions of the auxiliary data according to the encapsulated metadata describing the relevant portions.

Abstract: The present disclosure provides a method for detecting the focus of attention. The method includes: obtaining the face of a person in the first image, as well as the result of facial recognition; determining whether the distance between the person and the target is within an effective attention range; determining whether the face is frontal; determining whether the effective attention period is not shorter than a period threshold; detecting the focus of attention for the person to the target.

Abstract: A device and a method for classification using a pre-trained classification model and a computer readable storage medium are provided. The device is configured to extract, for each of multiple images in a target image group to be classified, a feature of the image using a feature extraction layer of the pre-trained classification model; calculate, for each of the multiple images, a contribution of the image to a classification result of the target image group using a contribution calculation layer of the pre-trained classification model; aggregate extracted features of the multiple images based on calculated contributions of the multiple images, to obtain an aggregated feature as a feature of the target image group; and classify the target image group based on the feature of the target image group.

Abstract: An image processing apparatus includes at least one processor executing the following processing including: image acquiring processing that acquires an image of an object in which a plurality of subjects, which are individually identifiable, are provided in a predetermined direction, the image including at least two subjects among the plurality of subjects; identifying processing that generates an information image including a feature amount of each of the subjects included in the image acquired in the image acquiring processing, and identifies each of the subjects by comparing with an information image stored in advance in memory; and output control processing that measures a distance between the subjects, each identified in the identifying processing, and controls to output a measurement result.

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: A computer, including a processor and a memory, the memory including instructions to be executed by the processor to acquire a first image from a first camera by illuminating a first object with a first light and determine an object status as one of a real object or a counterfeit object by comparing a first measure of pixel values corresponding to the first object to a threshold.

Abstract: Systems and techniques are provided for facial expression recognition. In some examples, a system receives an image frame corresponding to a face of a person. The system also determines, based on a three-dimensional model of the face, landmark feature information associated with landmark features of the face. The system then inputs, to at least one layer of a neural network trained for facial expression recognition, the image frame and the landmark feature information. The system further determines, using the neural network, a facial expression associated with the face.

Abstract: A user authentication method and a user authentication apparatus acquire an input image including a frontalized face of a user, calculate a confidence map including confidence values, for authenticating the user, corresponding to pixels with values maintained in a depth image of the frontalized face of the user among pixels included in the input image, extract a second feature vector from a second image generated based on the input image and the confidence map, acquire a first feature vector corresponding to an enrolled image, and perform authentication of the user based on a correlation between the first feature vector and the second feature vector.

Abstract: A detecting device includes a substrate, a plurality of detection electrodes provided on the substrate and arrayed in a first direction parallel to the substrate, a plurality of drive electrodes provided on the substrate and arrayed in a second direction intersecting the first direction, a second selection circuit configured to select a plurality of the detection electrodes based on selection signals, a first selection circuit configured to select a plurality of the drive electrodes, a detector coupled to the selected detection electrodes out of the detection electrodes, and a memory storing therein, as a set of output data, a plurality of detection signals output from the selected detection electrodes via the detector by the first selection circuit scanning the drive electrodes in one period when the second selection circuit selects the detection electrodes.

Abstract: Techniques are described for passive three-dimensional (3D) image sensing based on chromatic differentiation for use in object verification. For example, multiple sub-images correspond to 3D feature regions of an object. The sub-images can be analyzed to obtain respective sets of feature depth measurements (e.g., depth, textural signatures, etc.) based on multiple differentiated chromatic components of raw image sensor data captured from the object. A verification signal can be output as a function of comparing the respective sets of feature depth measurements from the plurality of characteristic sub-images to previously stored feature depth expectations, such that the verification signal indicates whether an identity of the object is verified and/or whether the object is a spoof.

Abstract: Systems and methods are disclosed for circular stitching of images. For example, methods may include accessing a first image captured using a first image sensor; accessing a second image captured using a second image sensor; determining a cost table for a circular stitching boundary that includes overlapping regions of the first image and the second image; determining an extended disparity profile based on a periodic extension of the cost table and a smoothness criterion, wherein the extended disparity profile has a length greater than the width of the cost table; determining a binocular disparity profile of a length equal to the width of the cost table based on a contiguous subsequence of the extended disparity profile; and stitching the first image and the second image using the binocular disparity profile to obtain a combined image.

Abstract: In order to provide an information processing apparatus in which a correction work time for coating information is shortened, an information processing apparatus for an imprint apparatus configured to perform an imprint process of forming a pattern on an imprint material (R) on a substrate (W) using a mold on the basis of coating information indicating a position of the imprint material (R) includes: at least one processor or circuit which function as: an obtaining unit configured to obtain inspection information regarding a result of an inspection of the substrate (W) which has been subjected to the imprint process; an analysis unit configured to analyze the inspection information and obtain analysis information associated with the result of the imprint process; and a display control unit configured to display at least any of the inspection information and the analysis information on a screen of a display apparatus at the same time with the coating information.

Abstract: Disclosed herein are methods and systems for determining whether a user engaged in an interactive video session is a genuine user or a potential impersonator by analyzing a plurality of consecutive images depicting the user while engaged in the video session to identify one or more dynamic facial patterns in the face of the user while his lips are moving. Each such dynamic facial pattern may express a movement of one or more of a plurality of wrinkles and/or other dynamic facial features (e.g., nostrils, distance between nostrils, ear, skin portion, muscle, etc.) in the face of the user. The user may be then determined to be genuine or not based on a comparison between the identified dynamic facial pattern(s) and one or more reference dynamic facial patterns.

Abstract: A method for authentication or identification of an individual, comprising the implementation by data processing means (11) of a terminal (1) of the following steps: (a) Obtaining of a visible image, an infrared image and a depth image on each of which a biometric feature of said individual appears; (b) Selection of at least one of said visible images, infrared image and depth image depending on the ambient lighting conditions; (c) Detection of said biometric feature of the individual in each image selected; (d) Fusion of the biometric feature(s) detected; and, (e) Authentication or identification of said individual on the basis of the result of the fusion of the biometric feature(s) detected.