Abstract: A visualized image display device includes an acquisition means for acquiring time-series feature data in which time-series data of a feature of an object in a video and an object ID are associated with each other, and classification data in which the object ID and a class ID labeled to the object are associated with each other; a selection means for selecting a class ID to be visualized, and a display control means for acquiring the object ID associated with the selected class ID from the classification data, acquiring time-series data associated with the acquired object ID from the time-series feature data, and on the basis of the acquired time-series data, displaying a feature image representing a temporal change of the feature of the object having the selected class ID, on a display unit.

Abstract: An authentication system according to one aspect of the present disclosure includes: at least one memory storing a set of instructions; and at least one processor configured to execute the set of instructions to: track an object included in a video captured by a first capture device; detect a candidate for biometric authentication in the object being tracked; determine whether biometric authentication has been performed for the candidate based on a record of biometric authentication performed for the object being tracked; and perform the biometric authentication for the candidate based on a video of an authentication part of the candidate when the biometric authentication has not been performed for the candidate, the video of the authentication part being captured by a second capture device having a capture range including a part of a capture range of the first capture device.

Abstract: In order to improve the learning performance of a neural network model, this image recognition model generating device is provided with an input image patch determining unit, a similar patch searching unit, a pixel value generating unit, and a convolution processing unit. The input image patch determining unit determines an input image patch containing a border region in contact with the outside of a boundary line of an input image. The similar patch searching unit searches for a similar patch that is similar to the input image patch. The pixel value generating unit generates a pixel value complementing the border region, on the basis of the similar patch. The convolution processing unit performs a convolution process from the generated pixel value and pixel values of the input image.

Abstract: A system includes: a sequential image string input unit configured to input a sequential image string having sequentiality; a reference image selection unit configured to select one or more images from the sequential image string as reference images; a variation calculation unit configured to select an adjacent reference image adjacent to the reference image from the sequential image string and calculate a variation between the reference image and the adjacent reference image; an image information regression unit configured to calculate class confidence by regression processing with the reference image as an input; a difference image information regression unit configured to calculate class confidence by regression processing with the variation as an input; a confidence integration unit configured to integrate class confidence calculated by the image information regression unit and class confidence calculated by the difference image information regression unit; and an output unit configured to output the inte

Abstract: The learning apparatus classifies target domain data into (N-c) classes based on unique features of the target domain data, classifies source domain data into N classes based on unique features of the source domain data, and classifies the target domain data and the source domain data into the N classes based on common features of the target domain data and the source domain data. Also, the learning apparatus calculates a first distance between the common features of the target domain data and the source domain data, and calculates a second distance between the unique features of the target domain data and the source domain data. Next, the learning apparatus updates parameters of a common feature extraction unit based on the first distance, and updates parameters of a target domain feature extraction unit and a source domain feature extraction unit based on the second distance.

Abstract: A learning apparatus includes a metric space learning unit and a case example storage unit. The metric space learning unit learns a metric space including feature vectors extracted from sets of attribute-attached image data for each combination of different attributes by using the sets of attribute-attached image data to which pieces of attribute information are added. The case example storage unit calculates feature vectors from sets of case example image data, and stores the feature vectors as case examples associated with the metric space.

Abstract: In order to ensure that similarity is detected with high accuracy, regardless of the types of images constituting a group of images to be evaluated for similarity, the image processing device includes difference calculation means 11 for deforming one of two or more images constituting an image group in one or more deforming ways, and calculating a degree of difference between the deformed image and the other image or images in the image group for each pixel using multiple ways for similarity evaluation, normalization means 12 for normalizing each degree of difference by each of the multiple ways for similarity evaluation, and difference integration means 15 for integrating normalized degrees of difference.

Abstract: A learning apparatus (500) according to the present invention includes a detection unit (510) that detects, as a candidate region of a learning target, a region detected by one of first detection processing of detecting an object region from a predetermined image and second detection processing of detecting a change region from background image information and the image, and not detected by the other, an output unit (520) that outputs at least a part of the candidate region as a labeling target, and a learning unit (530) that learns a model for performing the first detection processing or a model for performing the second detection processing by using the labeled candidate region as learning data.

Abstract: A surface property estimation system includes an image acquisition means for acquiring an image of a surface of an object, an estimation means for estimating a surface property from the acquired image by using an estimation model obtained through machine learning with use of an image of a surface of an object and a surface property shown by the image as training data, an extraction means for extracting, from the acquired image, a feature amount unique to the image, and a registration means for storing the estimated surface property and the extracted feature amount in a storage means in association with each other.

Abstract: A parameter estimation apparatus 10 is an apparatus for calculating a threshold for separating a plurality of data points into outliers and inliers and estimating a parameter fitting the inliers. The parameter estimation apparatus 10 includes: a parameter estimation unit 13 configured to estimate the parameter by using the plurality of data points as input; a threshold setting unit 14 configured to calculate the threshold based on statistical information of residuals of the data points; and a convergence determination unit 15 configured to determine whether or not convergence of the estimation of the parameter is reached based on the estimated parameter and the calculated threshold, and to cause the parameter estimation unit 13 and the threshold setting unit 14 to each execute processing again if the convergence determination unit 15 determines that convergence is not reached.

Abstract: An information collection server obtains relevant information relating to legislation, regulations, or standards (vehicle emissions control) from an external server group and a local server and provides the obtained relevant information to an information processing server. When the information processing server receives the relevant information from the information collection server, it performs conversion processing on each piece of information included in the relevant information in accordance with each piece of information to convert each piece of information into an index relating to a degree of influence on revision of the emissions control. The information processing server provides each resultant index to a prediction creation server. When the prediction creation server receives each resultant index from the information processing server, it predicts a stage of revision of the emissions control based on each index.

Abstract: A control device according to an aspect of the present disclosure includes: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: acquire an input image including an eye region that is a region of an eye part; estimate illuminance of the eye part from the acquired input image; and determine a light amount of illumination of visible light with which the eye part is irradiated in such a way that a pupil size of the eye part satisfies a size condition based on an illuminance size relationship that is a relationship between the illuminance and the pupil size.

Abstract: A first-aid information provision system of the example embodiments includes: an information display device that includes first capture means for capturing an iris image, code acquisition means for acquiring a code associated with the captured iris image, and code display means for displaying the acquired code; and an information output device that includes second capture means for imaging the code displayed by the information display device, first-aid information acquisition means for acquiring first-aid information about an individual associated with the iris image by using the imaged code, and first-aid information output means for outputting the first-aid information.

Abstract: The disclosure is inputting a first image obtained by capturing an object of authentication moving in a specific direction; inputting a second image at least for one eye obtained by capturing a right eye or a left eye of the object; determining whether the second image is of the left eye or the right eye of the object, based on information including the first image, and outputting a determination result associated with the second image as left/right information; comparing characteristic information relevant to the left/right information, the characteristic information being acquired from a memory that stores the characteristic information of a right eye and a left eye pertaining to object to be authenticated, with characteristic information associated with the left/right information, and calculating a verification score; and authenticating the object captured in the first image and the second image, based on the verification score, and outputting an authentication result.

Abstract: Please delete the Abstract of the Disclosure, and replace it with the following: An input image acquisition unit acquires a plurality of input images in which a specific detection target is captured by a plurality of different modalities. A perturbed image acquisition unit acquires a plurality of perturbed images in which at least one of the plurality of input images is perturbed. A detection processing unit detects a detection target included in the input images using each of the plurality of perturbed images and one of the plurality of input images that has not been perturbed, and acquires, for each of the plurality of perturbed images, a detection position of the detection target and a detection confidence level as detection results. An adjustment unit calculates, based on the detection positions and the confidence levels acquired for the plurality of perturbed images, an adjusted confidence level for each of the perturbed images using integrated parameters.

Abstract: An information providing device according to one aspect of the present disclosure includes: at least one memory storing a set of instructions; and at least one processor configured to execute the set of instructions to: receive a face image; determine whether a person in the face image is unsuitable for iris data acquisition based on the face image; and output information based on determining that the person is unsuitable for the iris data acquisition when the person is determined to be unsuitable for the iris data acquisition.

Abstract: An image acquisition unit (2) acquires an image obtained by capturing at least eyes of a target person. An object specifying unit (4) specifies an object in a line-of-sight direction of the target person using the acquired image. An incident light amount calculation unit (6) calculates an incident light amount representing an amount of light incident on the eyes of the target person using the acquired image. A reference pupil size determination unit (8) determines a reference pupil size based on the calculated incident light amount. A pupil size calculation unit (10) calculates a pupil size of the target person using the acquired image. An interest determination unit (12) determines an interest of the target person in the object by comparing the determined reference pupil size with the calculated pupil size.

Abstract: The disclosure is detecting an authentication target who is moving in a predetermined direction in a video; inputting a first image in which an entire body of the target; calculating characteristic information from an image of the entire body in the first image, comparing the calculated characteristic information with characteristic information of the entire body stored in first memory that stores characteristic information of entire bodies of targets, and extracting candidate information of the targets from the first memory based on a first authentication result; inputting a second image in which an iris of the target; and comparing characteristic information of irises stored in second memory that stores the characteristic information of the irises of targets with characteristic information of an iris from the second image, calculating a verification score, executing second authentication on the target in the second image based on the verification score, and outputting an authentication result.

Abstract: The disclosure is inputting a first image captured an image of an authentication target; inputting a second image captured an image of a right eye or a left eye of the target; determining whether the second image is of a left eye or a right eye of the target based on information including the first image, and outputting a determination result as left/right information in association with the second image; detecting an overlap between a region including the second image and a predetermined region in the first image; calculating a verification score by comparing characteristic information that are related to the left/right information with iris characteristic information calculated from the second image, and calculating a first weighted verification score obtained by weighting the verification score with a detection result; and authenticating a target in the second image based on the first weighted verification score, and outputting an authentication result.

Abstract: An information providing device according to one aspect of the present disclosure includes: at least one memory storing a set of instructions; and at least one processor configured to execute the set of instructions to: receive a face image; determine whether a person in the face image is unsuitable for iris data acquisition based on the face image; and output information based on determining that the person is unsuitable for the iris data acquisition when the person is determined to be unsuitable for the iris data acquisition.