Abstract:
Provided are a system, a method, and the like which contribute to more reliably and smoothly providing information relating to an authentication result to a person who has been subjected to authentication. An information provision system according to an embodiment of the present invention comprises: an authentication unit which authenticates an authentication subject, who is to be subjected to authentication, using a captured image of the authentication subject; a determination unit which, in accordance with information about the authentication subject or the conditions of the authentication subject, determines the transmission destination to which information relating to the authentication result is to be transmitted in order to notify the authentication subject of the authentication result; and a transmission unit which transmits the information to the determined transmission destination.
Abstract:
Disclosed is a model generation device capable of mitigating the risk of overlooking a phenomenon of interest in machine learning. The model generation device determines whether or not a label of a first data is similar to a label of a second data. The model generation device assigns the label of the second data to the first data when determining that the label of the first data is similar to the label of the second data based on a degree of similarity between observation information representing a state where the first data is observed and observation information representing a state where the second data is observed. The model generation device calculates model representing a relevance between data information containing the first data and the second data and label information containing the assigned label and the label of the second data.
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 processing device according to the present invention includes: a feature point sampling unit that generates, based on an initial value of a feature point used for registration of an object included in a target image to be processed, a feature point hypothesis that is a group of a plurality of the feature points in the target image; an image degradation unit that generates a degraded image that is a degraded image with degrading a reference image used for processing the target image, based on the feature point hypothesis and a degradation parameter for degrading an image; and a reliability calculation unit that calculates a reliability of the feature point hypothesis, based on the target image, the degraded image, and the feature point hypothesis.
Abstract:
An information processing device, apparatus, method and non-transitory computer-readable storage medium are disclosed. An information processing device may include a memory storing instructions, and at least one processor configured to process the instructions to generate a comparison image by transforming a reference image, associate the comparison image with a class variable representing an object included in the reference image, calculate a degree of difference between an input patch which is an image representing a sub-region of an input image and a comparison patch which is an image representing a sub-region of the comparison image, estimate a displacement vector between the input patch and the comparison patch, calculate a first degree of reliability corresponding to the displacement vector and the class variable on the basis of the displacement vector and the degree of difference, calculate a second degree of reliability for each comparison patch on the basis of the first degree of reliability, and identify the object is represented by the class variable associated with the comparison image including the comparison patch whose second degree of reliability is greater than a predetermined threshold value, as a recognition target.
Abstract:
An information processing apparatus may include a memory storing instructions and at least one processor configured to process the instructions to receive an input image. The input image includes either a first image or a provisional image created by iteratively image processing the first image. The instructions further provide for the processor to calculate a local variation of a focused pixel in the input image based on a difference in pixel value between the focused pixel and a surrounding pixel of the focused pixel, to calculate a filter coefficient for suppressing a variation between neighboring pixels in the input image based on the local variation, to create a degraded image by degrading the input image, to calculate a reconfiguration error between the input image and the degraded image, and to create the provisional image based on the filter coefficient and the reconfiguration error.
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:
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 integrated class confidence.
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 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.