Abstract: In one embodiment, a device forms a neural network envelope cell that comprises a plurality of convolution-based filters in series or parallel. The device constructs a convolutional neural network by stacking copies of the envelope cell in series. The device trains, using a training dataset of images, the convolutional neural network to perform image classification by iteratively collecting variance metrics for each filter in each envelope cell, pruning filters with low variance metrics from the convolutional neural network, and appending a new copy of the envelope cell into the convolutional neural network.

Abstract: The present invention relates to an apparatus (10) for feature suppression in dark field or phase contrast X-ray imaging. The apparatus comprises an input unit (20), a processing unit (30) and an output unit (40). The input unit is configured to provide the processing unit with an X-ray attenuation image of a region of interest of an object. The input unit is also configured to provide the processing unit with a dark field or phase contrast X-ray image of the region of interest of the object. The processing unit is further configured to identify a first feature in the X-ray attenuation image; to identify a second anatomical feature in the X-ray attenuation image; and to identify the second anatomical feature in the dark field or phase contrast X-ray image. The first feature is an obscuring anatomical feature depicted in the X-ray attenuation image with higher contrast than in the dark field or phase contrast X-ray image.

Abstract: Systems, methods, and computer-readable media are provided. Some embodiments include obtaining image data of a subject and a medical device, the medical device including fiducial markers, wherein the image data includes three-dimensional image data. Information is generated representing a three-dimensional shape based on a planned insertion point for performing a medical procedure. A cropping process is applied to the image data to generate cropped image data based on the three-dimensional shape. In some embodiments, the cropped image data includes image data of at least two of the fiducial markers. Fiducial marker objects are detected within the cropped image data, and the fiducial marker objects are registered by matching a model of the fiducial markers with the fiducial marker objects.

Abstract: The present invention refers to automatics and computing technology, namely to the field of processing images and video data, namely to correction the eyes image of interlocutors in course of video chats, video conferences with the purpose of gaze redirection. A method of correction of the image of eyes wherein the method obtains, at least, one frame with a face of a person, whereupon determines positions of eyes of the person in the image and forms two rectangular areas closely circumscribing the eyes, and finally replaces color components of each pixel in the eye areas for color components of a pixel shifted according to prediction of the predictor of machine learning. Technical effect of the present invention is rising of correction accuracy of the image of eyes with the purpose of gaze redirection, with decrease of resources required for the process of handling a video image.

Abstract: The present disclosure relates to a method for optical fingerprint recognition, a device for optical fingerprint recognition, and a computer-readable storage medium. The method may include: receiving optical signals obtained by sensors in a first area when detecting a finger to be recognized is placed in the first area; determining a plurality of fingerprint optical signals in a coverage area corresponding to the finger to be recognized in the optical signals; and recognizing the finger to be recognized according to the plurality of fingerprint optical signals in the coverage area.

Abstract: A method of processing optical coherence tomography (OCT) scans, comprising: receiving OCT data comprising an OCT signal indicative of the level of scattering in a sample, the OCT data including the OCT signal for at least one scan through the sample, with the OCT signal having been measured at varying depth and position through the sample in each scan; processing the OCT data for each scan with depth to produce a indicative depth scan representative of the OCT signal at each depth through all of the scans; fitting a curve to the indicative depth scan, the curve comprising a first term which exponentially decays with respect to the depth and a second term which depends on the noise in the OCT signal; and calculating a compensated intensity for the OCT signal at each point through each scan, the compensated intensity comprising a ratio of a term comprising a logarithm of the OCT signal to a term comprising the logarithm of the fitted curve.

Abstract: Various example implementations of the present invention are directed towards systems and methods to quantify biometric acquisition and identification. A test facility evaluates the acquisition by a biometric station of biometric information. Evaluations can relate to biometric information acquisition speed, rates of acquisition failure, rates of biometric information extraction failure, rates of biometric match failure, calculating a true identification rate, and/or calculating other metrics related to quantifying biometric acquisition and identification. The test facility can calculate an efficiency metric and an effectiveness metric of the quantification determinations, and output such results.

Abstract: A method, apparatus and computer program product are provided for iteratively establishing an optimized position of a feature from a plurality of images of the feature. Methods may include: receiving sensor data from at least one image sensor; processing the plurality of images to detect features within each of the plurality of images; for every combination of two images including the first feature, determining an estimated first feature position based on a triangulated position; establishing a spread of estimated first feature positions for the plurality of combinations of two images; determining a best-fit line passing through the spread of estimated first feature positions; iteratively minimizing a perpendicular error projection of each estimated first feature position relative to the best-fit line to obtain a reduced spread of optimized estimated first feature positions; and establishing from the reduced spread of optimized estimated feature positions an optimized estimated first feature position.

Abstract: A method for generating a three-dimensional (3D) lane model, the method including calculating a free space indicating a driving-allowed area based on a driving image captured from a vehicle camera, generating a dominant plane indicating plane information of a road based on either or both of depth information of the free space and a depth map corresponding to a front of the vehicle, and generating a 3D short-distance road model based on the dominant plane.

Abstract: An iris-based authentication method is provided. The method includes emitting light of an infrared wavelength band and obtaining an image based on the light of the infrared wavelength band, determining whether a specified condition is satisfied, if the specified condition is satisfied, performing user authentication (e.g., complex authentication) based on at least part of a face image and an iris image of the image that a biometric sensor obtains, or, if the specified condition is not satisfied, performing the user authentication (e.g., iris-only authentication) based on the iris image in the image that the biometric sensor obtains.

Abstract: A method for restoring images in a sequence of images, including, when it is applied to a first image in the image sequence: estimating an item of information representing a global motion of a background of the first image with respect to a second image; compensating for said global motion of the background in the second image in order to obtain an adjusted version of the second image, referred to as the adjusted second image; obtaining a contour of an object of the first image by applying a segmentation method using the adjusted second image; using the contour of the object thus obtained in order to estimate an item of information representing a global motion of the object; and applying to the first image an image restoration method using the information representing the estimated global motion of the background and the estimated global motion of the object.

Abstract: A radiation image capturing system includes a plurality of radiation image capturing apparatuses that each performs an image capturing operation to capture a radiation image based on radiation emitted from a radiation generating apparatus and transmitted through an object, a control apparatus that communicates with the plurality of radiation image capturing apparatuses, a calculation unit that calculates information about similarity between the radiation image and a reference image, and an image acquisition unit that acquires the radiation image from the radiation image capturing apparatus selected from the plurality of radiation image capturing apparatuses based on the information about similarity.

Abstract: A system for automatically annotating a map includes: a robot; a server operably connected to the robot; file storage configured to store files, the file storage operably connected to the server; an annotations database operably connected to the server, the annotations database comprising map annotations; an automatic map annotation service operably connected to the server, the automatic map annotation service configured to automatically do one or more of create a map of an item of interest and annotate a map of an item of interest; a queue of annotation requests operably connected to the automatic annotation service; and a computer operably connected to the server, the computer comprising a graphic user interface (GUI) usable by a human user.

Abstract: A mobile terminal according to one embodiment of the present disclosure comprises: a display unit including a fingerprint recognizable area in which a fingerprint can be recognized, and a fingerprint non-recognition area in which the fingerprint cannot be recognized; a fingerprint recognition sensor embedded on the lower end of the display unit so as to correspond to the fingerprint recognizable area, and recognizing the fingerprint inputted to the display unit; and a control unit for controlling the fingerprint recognition sensor such that the fingerprint inputted simultaneously with a drag operation is recognized if the drag operation, of moving the finger from any one of the fingerprint recognizable area and the fingerprint non-recognition area to the other one while making contact therewith, is inputted into the display unit, and for executing a security home screen or a basic home screen according to whether fingerprint authentication performed on the basis of the fingerprint recognized by the fingerprin

Abstract: A method of automatically detecting anomaly from aerial images of an object of interest is provided. The method may include generating a data coding model corresponding to a category of assets by training a neural network with a training set of digital images depicting an asset in a state that is free from anomalies. The method may further include receiving a target digital image depicting a target asset, and reconstructing the target digital image using the data coding model to generate a decoded target digital image associated with the state that is free from anomalies. The data coding model may be self-supervised to learn to reconstruct itself to an anomaly-free state. The method may also include comparing the target digital image to the decoded target digital image to generate a difference map and, in response to a determination that the difference map depicts any anomaly, generating anomaly alert data.

Abstract: Techniques are disclosed for systems and methods to provide identity verification for protected services. An identity verification system includes an authenticator device configured to provide a visible spectrum optical sequence including an authentication identifier to an authentication station. The authentication station includes an optical sensor configured to capture a time sequence of visible spectrum image data associated with a validated user, and a logic device configured to receive a visible spectrum optical sequence from the optical sensor, verify the authentication identifier, and execute a protected process associated with the verified authentication identifier. The authenticator device includes an optical transmitter and a logic device configured determine a visible spectrum optical sequence comprising the authentication identifier and to generate the visible spectrum optical sequence using the optical transmitter.

Abstract: Systems and methods for moving point detection for point clouds. Some implementations may include obtaining a sequence of point clouds, wherein the sequence of point clouds includes a current point cloud, a previous point cloud that precedes the current point cloud, and a next point cloud that follows the current point cloud; inputting a voxelized representation of the current point cloud to a forward-pass recurrent neural network with a hidden state based on the previous point cloud to obtain a first voxelized activation; inputting the voxelized representation of the current point cloud to a backward-pass recurrent neural network with a hidden state based on the next point cloud to obtain a second voxelized activation; combining the first voxelized activation and the second voxelized activation to obtain a prediction of whether respective points are moving or static; and updating the current point cloud based on the prediction.

Abstract: A device for acquisition of particles present in a sample includes a spatially coherent light source, an optical system, and an image sensor placed in the focal plane of the optical system. The image sensor is configured to capture an intensity image. A computational unit of the device is configured to construct a series of electromagnetic propagation matrices obtained for a plurality of defocusing offsets relative to a plane of focus of the optics. The computational unit is also configured to determine a first average focused electromagnetic matrix for the particles from the series of electromagnetic matrices, identifying at least one of the particles in the first electromagnetic matrix and storing the coordinates of said particle, and determining a second electromagnetic matrix at a distance of focus on a particle identified from the components of the series of electromagnetic matrices having the stored coordinates.

Abstract: An information processing apparatus includes a determination, first, second and third receiving, and first and second checking units, and a controller. When a determination result matches a first determination result, the first checking unit outputs a matching determination result as the final output. The second checking unit checks the first determination result against a second. The first and second determination results are respectively received by the first and second receiving units. When the first determination result matches the second, the second checking unit outputs the matching determination result as the final output. When the input information is received, the controller operates the determination, first receiving, and first checking units. When it is determined that the determination result does not match the first determination result, the controller operates selectively one of a unit set and the third receiving unit. The unit set is constituted by the second receiving and checking units.

Abstract: A computer-implemented method of determining relative velocity between a vehicle and an object. The method includes receiving sensor data generated by one or more sensors of the vehicle configured to sense an environment by following a scan pattern comprising component scan lines. The method includes obtaining, based on the sensor data, a point cloud frame. Additionally, the method includes identifying a first pixel and a second pixel that are co-located within a field of regard and overlap a point cloud object within the point cloud frame and calculating a difference between a depth associated with the first pixel and a depth associated with the second pixel. The method includes determining a relative velocity of the point cloud object by dividing the difference in depth data by a time difference between when the depth associated with the first pixel was sensed and the depth associated with the second pixel was sensed.