Abstract: One or more computing devices, systems, and/or methods are provided. One or more videos associated with a user may be analyzed to determine a first set of features of the user associated with a first emotion of the user and/or a second set of features of the user associated with a second emotion of the user. A first user emotion profile associated with the user may be generated based upon the first set of features and/or the second set of features. A second video may be presented via a graphical user interface of a first client device. The user may be identified within the second video. It may be determined, based upon the second video and/or the first user emotion profile, that the user is associated with the first emotion. A representation of the first emotion may be displayed via the graphical user interface of the first client device.

Abstract: A method of authentication using surface paper texture includes steps of capturing a topographic pattern image of a surface of a region of interest of the paper artifact and extracting a plurality of specific features from the captured topographic pattern image. The method further identifies the location of the specific features of the paper artifact from the captured topographic pattern image. A bit map of the identified location of the specific features is generated. Then, a reference image of a reference bit map printed on the region of interest of the paper artifact is captured. Finally, the method compares the generated bit map with the captured reference bit map to generate a score. The score of the comparison determines the level of authentication. The method provides an offline method of authentication.

Abstract: A guidance processing apparatus (100) includes an information acquisition unit (101) that acquires a plurality of different pieces of guidance information on the basis of states of a plurality of people within one or more images, and a control unit (102) that performs control of a plurality of target devices present in different spaces or time division control of a target device so as to set a plurality of different states corresponding to the plurality of pieces of guidance information.

Abstract: There is provided systems, methods and computer program products for generating motion blur on image frames, comprising: obtaining gaze data related to an eye movement between consecutive images, determining movement of at least one object in relation to said gaze data by calculating the difference in position of said at least one object and said gaze data between the image frames, forming a motion blur vector and applying a motion blur on an image frame based on said motion blur vector.

Abstract: The present disclosure relates to systems and methods for image splicing. The systems and methods may acquire a first image and a second image, determine a plurality of first feature points in a first region of the first image, determine a plurality of second feature points in a second region of the second image, then match the plurality of first feature points with the plurality of second feature points to generate a plurality of point pairs. Based on the plurality of point pairs, a third region on the first image and a fourth region on the second image may be determined. Finally, a third image may be generated based on the first image and the second image, wherein the third region of the first image may overlap with the fourth region of the second image in the third image.

Abstract: There is provided an information processing apparatus, an information processing method, and a program that can optimize information output in response to an environment in a space, the information processing apparatus including: a recognition unit that recognizes a situation in a space based on sensor data obtained by sensing the space in which a content is output; and a determination unit that determines an output scheme of the content based on a result of the recognition and an analysis result of related information of the content.

Abstract: A face authentication apparatus includes a face image acquisition unit that acquires, as a first face image, a face image of a user who moves from a first area to a second area via a gate provided between the first area and the second area, a collation unit that performs face authentication, a flow rate measurement unit that measures a flow rate of users who move from the first area to the second area via the gate and a flow rate of users who move from the second area to the first area via the gate, and a security level determination unit that determines the security level of the first area and the security level of the second area on the basis of the flow rates measured.

Abstract: Computer vision systems and methods for localizing image forgery are provided. The system generates a constrained convolution via a plurality of learned rich filters. The system trains a convolutional neural network with the constrained convolution and a plurality of images of a dataset to learn a low level representation of each image among the plurality of images. The low level representation is indicative of a statistical signature of at least one source camera model of each image. The system can determine a splicing manipulation localization by the trained convolutional neural network.

Abstract: A tunable signal sampling system includes a computing platform having a hardware processor and a memory storing a software code that when executed receives a communications signal, identifies data partitions included in the communications signal, performs, using a first predetermined metric, a first set of comparisons each comparing a different sequential pair of the data partitions with each other, and selects, based on the first set of comparisons, a subset of the data partitions as candidate sample partitions of the communications signal. The software code also determines multiple default sample partitions of the communications signal, performs, using a second predetermined metric, a second set of comparisons each comparing a different one of the default sample partitions with a respective one of the candidate sample partitions, and extracts, using a predetermined weighting factor applied to the results of the second set of comparisons, a sample of the communications signal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining image data of an identification (ID) document and identifying a pattern of the ID document based on analysis of the image data against a predefined patterns for a particular type of document. An identifier engine of the system computes a frequency metric that defines how often the pattern reoccurs at the ID document and generates a unique identifier for the ID document based on the computed frequency metric. The unique identifier is stored at a digital fingerprint database of the system as a digital fingerprint for the ID document.

Abstract: An image encoding method including: a constraint information generating step of generating tile constraint information indicating whether or not there is a constraint in filtering on boundaries between adjacent tiles among a plurality of tiles obtained by dividing a picture, and storing the tile constraint information into a sequence parameter set; and a filter information generating step of generating, for each of the boundaries, one of a plurality of filter information items respectively indicating whether or not filtering is executed on the boundaries, and storing the plurality of filter information items into a plurality of picture parameter sets, wherein, in the filter information generating step, the plurality of filter information items which indicate identical content are generated when the tile constraint information indicates that there is the constraint in the filtering.

Abstract: A traveling environment recognition apparatus includes a first detector that detects an object in a first region outside a vehicle, a second detector that detects an object in a second search region that at least partly overlaps with the first region, a determiner that determines whether two objects respectively detected by the two detectors are a same object, in an overlapping region of the search regions; and a recognizer that integrates the detected objects, and to recognize the detected objects as one fusion object. The recognizer compares a threshold with a parameter based on distances from the vehicle to the detected objects, to recognize the fusion object using a worst value of detection results of the detected objects when the detected objects are near the vehicle, and recognize the fusion object using a mean value of the detection results when the detected objects are far from the vehicle.

Abstract: A mechanism is described for facilitating on-the-fly deep learning in machine learning for autonomous machines. A method of embodiments, as described herein, includes detecting an output associated with a first deep network serving as a user-independent model associated with learning of one or more neural networks at a computing device having a processor coupled to memory. The method may further include automatically generating training data for a second deep network serving as a user-dependent model, where the training data is generated based on the output. The method may further include merging the user-independent model with the user-dependent model into a single joint model.

Abstract: A method and apparatus for sorting is described, and which includes providing a product stream formed of individual objects of interest having feature aspects which can be detected; generating multiple images of each of the respective objects of interest; classifying the feature aspects of the objects of interest; identifying complementary images by analyzing some of the multiplicity of images; fusing the complementary images to form an aggregated region representation of the complementary images; and sorting the respective objects of interest based at least in part upon the aggregated region representation which is formed.

Abstract: The present disclosure relates to an image composite system that employs a generative adversarial network to generate realistic composite images. For example, in one or more embodiments, the image composite system trains a geometric prediction neural network using an adversarial discrimination neural network to learn warp parameters that provide correct geometric alignment of foreground objects with respect to a background image. Once trained, the determined warp parameters provide realistic geometric corrections to foreground objects such that the warped foreground objects appear to blend into background images naturally when composited together.

Abstract: The present invention provides digitally driven methods to conveniently and efficiently monitor and evaluate the positions of a patient's teeth during the course of orthodontic treatment. In an exemplary embodiment, an initial set of 3D digital data representing a patient's dental structure is provided by means of an X-ray radiograph and/or an intraoral scan. Then during the course of treatment, a reduced image representing part of the dental structure may be quickly provided using a bite plate or a low resolution intraoral scan. A three-dimensional (3D) image of the full dental structure is subsequently rendered or “reconstructed” by registering elements of the initial image with corresponding elements of the reduced image. By reconstructing the dental structure from the reduced image, the treating professional can provide a precise, manipulable 3D image of the patient's complete dental structure for diagnostic and treatment planning purposes.

Abstract: The present disclosure provides a computer implemented method and system for compensating for cloud cover to allow the build-up of composite, cloud free images of a particular geographic area. The disclosure takes satellite or aerial image data as an input and temporally stacks the images for a particular geographic area, with the most recent image at the top. The time for the composite image to be produced (which may be the present time, or may be a time from the past) is defined as a temporal projection plane. The most recent image prior to or temporally proximate to this plane is analysed to identify any areas obscured by clouds. Cloud free areas of the most recent image are projected onto the temporal projection plane. For the identified obscured areas, older, cloud free images in the stack are projected onto the temporal projection plane to fill the obscured areas. This forms a cloud free composite image at the defined temporal projection plane.

Abstract: The present disclosure generally relates to a device and a method of decoding a color picture from a bitstream.

Abstract: A method of detecting an anomaly is provided, including dividing each frame of a video stream into a plurality of cells; in each cell formulate statistics based on metadata generated for the frame, the metadata related to presence of an object in the cell, velocity of objects in the cell, direction of motion of objects in the cell, and classification of objects in the cell; and using the formulated statistics to determine when the anomalous activity has occurred in one of the cells of the plurality of cells.

Abstract: An electronic device includes circuitry that determines probability map information for a first image, based on application of a neural network model on the first image. The neural network model is trained to detect one or more objects based on a plurality of images associated with the one or more objects. The probability map information indicates a probability value for each pixel in the first image. A region corresponding to the one or more objects is detected in the first image based on the probability map information. A first set of sub-images is determined from the detected region, based on application of a stochastic optimization function on the probability map information. The one or more objects are detected from a second set of sub-images of the first set of sub-images, based on application of the neural network model on the second set of sub-images.