Abstract: Systems and methods are disclosed including a computerized system, comprising: a computer system running image display and analysis software that when executed by the computer system causes the computer system to: display an oblique image; reference positional data for the oblique image; create a ground plane for the oblique image, the ground plane comprising a plurality of facets, the facets conforming to a topography of an area captured within the oblique image; receive a selection of at least two pixels within the oblique image; and calculate a desired measurement using the selection of the at least two pixels and the ground plane, the desired measurement taking into account changes within the topography of the area captured within the oblique image.

Abstract: A method for enhancing an image for facial recognition comprises capturing an image of the face with a polarizer and correcting the polarized image for non-uniformity. Stokes Parameters S0, S1, S2 are obtained by weighted subtraction of the polarized image to form Stokes images. DoLP is computed from the Stokes images, and facial recognition algorithms are applied to the DoLP image. A system for enhancing images for facial recognition comprises a polarimeter configured to record polarized image data of a subject's face, a signal processing unit and logic configured to receive and store in memory the image data from the polarimeter, calculate Stokes parameters from the image data, and compute a DoLP image from the Stokes parameters.

Abstract: Filtering a data set including a plurality of image frames to form a reduced “key frame” data set including a reduced plurality of “key” image frames that is suitable for use in training an artificial intelligence (AI) or machine learning (ML) system, including: removing an image frame from the plurality of image frames of the data set if a structural similarity metric of the image frame with respect to another image frame exceeds a predetermined threshold, thereby forming a reduced data set including a reduced plurality of image frames; and analyzing an object/semantic content of each of the reduced plurality of images using a plurality of dissimilar expert models and designating any image frames for which the plurality of expert models disagree related to the object/semantic content as “key” image frames, thereby forming the reduced “key frame” data set including the reduced plurality of “key” image frames.

Abstract: A system and method for identifying missing required data elements in an electronic document. The method includes analyzing the electronic document to identify at least one data element; determining, based on the identified at least one data element and at least one electronic document requirement, whether there is at least one required data element missing from the electronic document; generating a query based on the identified at least one data element upon determining that there is at least one required data element missing from the electronic document; querying a database using the generated query; and modifying, based on a response to the query, the electronic document to include the at least one missing required data element.

Abstract: Smoking-related article inspection systems and associated methods are disclosed herein. In some aspects, the systems include an x-ray imaging device configured to capture at least one image of the smoking-related articles, a smoking-related article transporting device configured to sequentially introduce the smoking-related articles into the imaging zone; and an analysis unit in communication with the x-ray imaging device and configured to analyze the at least one image captured by the x-ray imaging device for each of the smoking-related articles, the analysis unit being configured to execute: an inspection tool to determine values for one or more parameters of each of the smoking-related articles based on the analysis of the at least one image; and a comparison tool to determine an acceptability of the smoking-related articles for further processing based on comparing the determined values for the one or more parameters to ideal values for the one or more parameters.

Abstract: An example of the present disclosure provides methods, apparatuses and devices for magnifying a feature map, and a computer readable storage medium. The method includes: receiving a source feature map to be magnified; obtaining N reassembly kernels corresponding to each source position in the source feature map by performing convolution on the source feature map, wherein N refers to a square of a magnification factor of the source feature map; obtaining, for each of the reassembly kernels, a normalized reassembly kernel by performing normalization; obtaining, for each source position in the source feature map, N reassembly features corresponding to the source position by reassembling features of a reassembly region determined according to the source position with N normalized reassembly kernels corresponding to the source position; and generating a target feature map according to the N reassembly features corresponding to each source position in the source feature map.

Abstract: Methods, devices and systems for training a pattern recognition system are described. In one example, a method for training a sign language translation system includes generating a three-dimensional (3D) scene that includes a 3D model simulating a gesture that represents a letter, a word, or a phrase in a sign language. The method includes obtaining a value indicative of a total number of training images to be generated, using the value indicative of the total number of training images to determine a plurality of variations of the 3D scene for generating of the training images, applying each of plurality of variations to the 3D scene to produce a plurality of modified 3D scenes, and capturing an image of each of the plurality of modified 3D scenes to form the training images for a neural network of the sign language translation system.

Abstract: A suspiciousness degree estimation model generation device includes: a clustering unit that performs clustering on an input face image based on the feature extracted from the face image; and a suspiciousness degree estimation model generation unit that generates a suspiciousness degree estimation model used for estimating the suspiciousness degree of an estimation target person, based on the result of clustering by the clustering unit and suspiciousness degree information that is previously associated with a face image included by the clustering result and that shows the suspiciousness degree of a person shown by the face image.

Abstract: A suspiciousness degree estimation model generation device includes: a clustering unit that performs clustering on an input face image based on the feature extracted from the face image; and a suspiciousness degree estimation model generation unit that generates a suspiciousness degree estimation model used for estimating the suspiciousness degree of an estimation target person, based on the result of clustering by the clustering unit and suspiciousness degree information that is previously associated with a face image included by the clustering result and that shows the suspiciousness degree of a person shown by the face image.

Abstract: A suspiciousness degree estimation model generation device includes: a clustering unit that performs clustering on an input face image based on the feature extracted from the face image; and a suspiciousness degree estimation model generation unit that generates a suspiciousness degree estimation model used for estimating the suspiciousness degree of an estimation target person, based on the result of clustering by the clustering unit and suspiciousness degree information that is previously associated with a face image included by the clustering result and that shows the suspiciousness degree of a person shown by the face image.

Abstract: Provided is a super-resolution image sensor and a producing method thereof such that, on the basis of not changing the arrangement of the image sensitive unit array of the image sensor, by means of the existing micro-lens manufacture techniques, the imaging resolution can be increased by offsetting micro-lens rows in a micro-lens array that covers upon the image sensitive unit array. In some examples, a super-resolution image sensor comprises an image sensitive unit array having image sensitive unit rows aligned with one another, and a micro-lens array covering upon the image sensitive unit array. Relative to a reference micro-lens row in the micro-lens array, the other micro-lens rows are regularly offset. Each micro-lens unit in the reference micro-lens row is center aligned with a corresponding image sensitive unit in a reference image sensitive unit row.

Abstract: Provided is a a method for evaluating a document, including establishing, by a processor of a computing system, a video data link for transmitting a video signal between a second data processing device comprising a video recording device, and a first data processing device, generating, by the processor, an operation identification number assigned to user data, wherein the operating identification number is tamper-proof, transmitting, by the processor, the operating identification number to the second data processing device, transmitting, by the second data processing device, the user data to the first data processing device, transmitting, by the second data processing device, an image of a document captured by means of the video recording device to the first data processing device via the video data link; and evaluating the document.

Abstract: In accordance with disclosed embodiments, an image processing method includes performing a first scan in a first direction on a first list of pixels in which, for each pixel in the first list, a feature point property is compared with a corresponding feature point property of each of a first set of neighboring pixels, performing a second scan in a second direction on the first list of pixels in which, for each pixel in the first list, a feature point property is compared with a corresponding feature point property of each of a second set of neighboring pixels, using the results of the first and second scans to identify pixels from the first list to be suppressed, and forming a second list of pixels that includes pixels from the first list that are not identified as pixels to be suppressed. The second list represents a non-maxima suppressed list.

Abstract: Described herein are methods and systems for detecting clouds in satellite imagery captured using first and second sensor arrays that are carried by a satellite and physically offset from one another on the satellite. Movement mask data is produced based first image data and the second image data, obtained, respectively, using the first and second sensor arrays carried by the satellite. Cloud mask data is produced based on spectral information included one of the first and second image data. Cloud detection data is produced based on the movement mask data and the cloud mask data, the cloud detection data indicating where it is likely, based on both the movement mask data and the cloud mask data, that one or more clouds are represented within one of the first and second image data. The cloud detection data can be used in various ways to account for the clouds included within the satellite imagery.

Abstract: A method for training, using a plurality of training images with corresponding six degrees of freedom camera pose for a given environment and a plurality of reference images, each reference image depicting an object-of-interest in the given environment and having a corresponding two-dimensional to three-dimensional correspondence for the given environment, a neural network to provide visual localization by: for each training image, detecting and segmenting object-of-interest in the training image; generating a set of two-dimensional to two-dimensional matches between the detected and segmented objects-of-interest and corresponding reference images; generating a set of two-dimensional to three-dimensional matches from the generated set of two-dimensional to two-dimensional matches and the two-dimensional to three-dimensional correspondences corresponding to the reference images; and determining localization, for each training image, by solving a perspective-n-point problem using the generated set of two-dimens

Abstract: The present disclosure relates to a method of measuring wear of a disk in an aircraft brake having a wear indicator that is movably mounted on a stationary portion of the aircraft brake and that moves progressively with increasing wear of the disk. The method includes using a picture-taking appliance to take at least one photograph of the wear indicator while an aircraft is stationary on the ground, and estimating a position of the wear indicator and a wear level of the disk by analyzing the photograph.

Abstract: A system and method. The system may include a display, an image generator configured to output a stream of image data, an aircraft state sensor configured to output aircraft state data, and at least one processor. The at least one processor may be configured to: receive the stream of image data; compute an optical flow on the stream of the image data resulting in image-based motion vectors (MVs); receive the aircraft state data; compute expected MVs based on the aircraft state data; compare the expected MVs with the image-based MVs; determine whether at least some of the stream of the image data fails a predetermined assurance level based on a comparison of the expected MVs with the image-based MVs; and upon a determination that at least a portion of the stream of the image data fails the predetermined assurance level, transmit or implement a system response.

Abstract: Methods and systems for evaluating the quality of a geospatial data set are provided. Regions of a data set may be selected for review based on statistical methods and a distribution of map features in the data set. Based on errors identified in the selected regions, one or more quality scores may be generated for the data set. Quality scores may be applied toward assessing the utility of the data set against an intended use. Quality scores may be modified in response to an indication that certain feature classes are not relevant for an intended use of the data set. Information associated with the review of a data set may be tracked and stored.

Abstract: Implementations described herein relate to methods, devices, and computer-readable media to perform gating for video analysis. In some implementations, a computer-implemented method includes obtaining a video comprising a plurality of frames and corresponding audio. The method further includes performing sampling to select a subset of the plurality of frames based on a target frame rate and extracting a respective audio spectrogram for each frame in the subset of the plurality of frames. The method further includes reducing resolution of the subset of the plurality of frames. The method further includes applying a machine-learning based gating model to the subset of the plurality of frames and corresponding audio spectrograms and obtaining, as output of the gating model, an indication of whether to analyze the video to add one or more video annotations.

Abstract: A method for determining assignment data is carried out in a method for determining a geometry calibration. The 3D calibration phantom features a calibration object with a number of calibration elements, which are arranged so that a descriptor based on the spatial arrangement is projectively invariant. Based upon the descriptor the calibration elements mapped in the 2D transmission element can be assigned to the calibration elements of the calibration object, so that the geometry calibration is determined on the basis of this assignment and the arrangement of the calibration elements in the three-dimensional space as well as on the 2D image.