Abstract: Systems, devices, media and methods are presented for generating biometric image data. In one example, a system accesses a set of images stored on a mobile computing device. The system identifies one or more faces depicted in the set of images and generates a set of face images from the set of images. The system determines a set of positions of a set of facial features depicted within the set of face images and generates a set of biometric reference maps based on the set of positions. The system transmits the set of face images to a reference server and stores the set of biometric reference maps on the mobile computing device.

Abstract: In various examples, estimated field of view or gaze information of a user may be projected external to a vehicle and compared to vehicle perception information corresponding to an environment outside of the vehicle. As a result, interior monitoring of a driver or occupant of the vehicle may be used to determine whether the driver or occupant has processed or seen certain object types, environmental conditions, or other information exterior to the vehicle. For a more holistic understanding of the state of the user, attentiveness and/or cognitive load of the user may be monitored to determine whether one or more actions should be taken. As a result, notifications, AEB system activations, and/or other actions may be determined based on a more complete state of the user as determined based on cognitive load, attentiveness, and/or a comparison between external perception of the vehicle and estimated perception of the user.

Abstract: One variation of a method for augmenting a digital procedure for production of pharmacological materials with automatic verification of objects includes: initializing a digital procedure containing a sequence of instructional blocks; and populating a instructional block with a instruction in a set of formats and a set of target objects. The method further includes, in response to an operator initiating an instance of the instructional block: accessing video feeds of the operator performing the instructional block; identifying a target object in a target frame from the video feeds; extracting visual features from the target frame; calculating an identification score for the target object based on the visual features; in response to the identification score falling below a confidence threshold, applying a fiducial to the target object; and linking the target object to the fiducial in the instructional block.

Abstract: Provided is a damage diagram creation support method, which includes: acquiring information on a region having internal damage to a structure within an inspection target region; acquiring a visible light image obtained by imaging the inspection target region with a visible light camera; detecting fissuring appearing on a surface of the structure in the visible light image; and creating a damage diagram in which the fissuring detected in the visible light image is traced. Also provided is a damage diagram creation support device capable of appropriately recording a detection result of fissuring automatically detected from an image.

Abstract: The present disclosure includes systems, methods, and computer-readable storage media facilitating multi-target tracking with dependent likelihood structures. To facilitate tracking, sensor data associated with an environment that a vehicle is located in may be received. A set of candidate hypotheses may be obtained based on the sensor data. Each candidate hypothesis in the set of candidate hypotheses may include track and measurement information representative of candidate locations for one or more targets. The set of candidate hypotheses are evaluated against at least one criterion. A ranked set of hypotheses are determined based on the evaluation of the set of candidate hypothesis against the at least one criterion. The ranked set of hypotheses may include a subset of hypotheses selected from among the set of candidate hypotheses and may be used to estimate a location of each of the one or more targets.

Abstract: According to one embodiment, an information processing apparatus includes processing circuitry. The processing circuitry calculates a plurality of bases by performing a basis conversion on signal data. The processing circuitry selects one or more specific bases with contribution rates lower than a reference from among the bases. The processing circuitry executes data processing utilizing the specific bases.

Abstract: A positioning method, a positioning device, and a processing method for wafer are provided. The wafer includes a plurality of dies. The positioning method for wafer includes: obtaining a first reference image of the wafer and obtaining a first rotation angle based on the first reference image and a first positioning template; causing the wafer to rotate according to the first rotation angle; obtaining a second reference image of the wafer rotated according to the first rotation angle and obtaining a second rotation angle based on the second reference image and the first positioning template; causing the wafer to rotate according to the second rotation angle; obtaining a third reference image of the wafer rotated according to the second rotation angle and obtaining position information of each die contained in the wafer based on the third reference image and a second positioning template.

Abstract: A method for unsupervised learning of drivable space, the method may include receiving, by a processing circuit, an image of an environment of a vehicle; searching, in the image and by the processing circuit, for a drivable space within the environment of the vehicle, wherein the drivable space is associated with a statistically significant drivable space behavior; wherein the association is learnt by applying an unsupervised learning process; and responding, by the processing circuit, to a finding of the drivable space.

Abstract: Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive from a network entity first control signaling identifying, of multiple cell groups configured at the UE, an inter-cell mobility configuration for a set of one or more cell groups for use at the UE. In some examples, each cell group of the multiple cell groups may include a primary cell (PCell) and zero or more secondary cells (SCells). The UE may transmit a measurement report for each cell group of the set of one or more cell groups for inter-cell mobility. The UE may receive, at least in part in response to transmitting the measurement report, second control signaling activating or deactivating a primary cell group for inter-cell mobility from one or more cell groups of the set of one or more cell groups.

Abstract: A method for detecting defects includes steps of: (1) calculating an average value for intensity of CT image voxels in a neighborhood; (2) calculating a difference value for the intensity of the voxels in the neighborhood; (3) calculating a standard deviation for the intensity of the voxels in the neighborhood; (4) calculating a z-score for each one of the voxels; (5) identifying a cluster of neighboring ones of the voxels; (6) determining a cluster-boundary parameter of the cluster; and (7) classifying the cluster as a defect when the cluster-boundary parameter of the cluster is above a parameter threshold.

Abstract: Techniques for determining ground surface voxels based on multiresolution planes are discussed herein. Such multiresolution planes may be generated, validated, and used to connect voxels associated with the ground. In some examples, a vehicle may use capture or otherwise receive lidar data while traversing within a driving environment. The vehicle may associate the lidar data with a voxel space. Voxels can be associated with a cell of a multiresolution grid and the vehicle may determine multiresolution planes associated with the multiresolution space. For example, the vehicle may determine a first plane associated with a first resolution level, in addition to determining a plurality of planes associated with a second resolution level. The vehicle may determine the validity of the plane(s) at the various resolution levels. Based on the validity of the planes, the vehicle may connect the valid planes that are associated with the ground surface.

Abstract: The application discloses a method, a device, a system and a computer storage medium for obtaining the CT perfusion imaging parameter maps of brain. The method includes: obtaining CT perfusion images, pre-processing the CT perfusion images, and obtaining discrete contrast agent concentration curve C(n) of each pixel point in the brain tissue; reading the acquisition time information of the CT perfusion images to obtain the acquisition time array T(n); intercepting the acquisition time array T(n) to obtain the relative acquisition time array t(n); combining the discrete contrast agent concentration curve C(n) with the corresponding relative acquisition time array t(n) to obtain the discrete time-concentration curve C(tn) of each pixel point in the brain tissue; after fitting or interpolating the discrete time-concentration curve C(tn), re-discretizing at the same time interval, and obtaining the discrete time-concentration curve C(n)? of each pixel point in brain tissue.

Abstract: A method for stray light compensation is disclosed. The method comprising: acquiring a first image with a first imaging device covering a first field-of-view; acquiring a second image with a second imaging device covering a second field-of-view, wherein the second field-of-view is larger than the first field-of-view and wherein the first field-of-view is included in the second field-of-view; estimating stray light components in pixels of the first image from pixel data of pixels in the second image; and compensating for stray light in the first image by subtracting the estimated stray light components in pixels of the first image. Also, a system for stray light compensation is disclosed.

Abstract: An ocular fundus image processing device acquires a first image generated by irradiating an ocular fundus of a subject with excitation light of a blue wavelength and a second image generated by irradiating the ocular fundus with excitation light of a green wavelength, generates three trained models for predicting a correction factor for calculating a quantity of macular pigment of the subject from input images including the first image and the second image through training using three different initial values, predicts three correction factors by inputting the input images including the first image and the second image to the three trained models, calculates a statistical value of the three correction factors and derives the statistical value as the correction factor of the subject, and calculates a quantity of macular pigment of the subject on the basis of the first image and the correction factor of the subject.

Abstract: An image processing system accesses an image depicting a particular object. The system identifies a location of the particular object within the image and defines, based on the identified location of the particular object within the image, a focal region of the image. The focal region can be used to modify the image for delivery and presentation on a webpage or software application.

Abstract: An image processing method includes acquiring an image frame; tracking a face region of a user based on first prior information obtained from at least one previous frame of the image frame; based on a determination that tracking of the face region based on the first prior information has failed, setting a scan region in the image frame based on second prior information obtained from the at least one previous frame; and detecting the face region in the image frame based on the scan region.

Abstract: This application provides an image processing method, a network training method, and a related device, and relates to image processing technologies in the artificial intelligence field. The method includes: inputting a first image including a first vehicle into an image processing network to obtain a first result output by the image processing network, where the first result includes location information of a two-dimensional (2D) bounding frame of the first vehicle, coordinates of a wheel of the first vehicle, and a first angle of the first vehicle, and the first angle of the first vehicle indicates an included angle between a side line of the first vehicle and a first axis of the first image; and generating location information of a three-dimensional (3D) outer bounding box of the first vehicle based on the first result.

Abstract: A video image interference detection method includes the following steps: acquiring a background image and a current frame image; constructing an edge image of the background image and an edge image of the current frame image respectively; intersecting the edge image of the background image and the edge image of the current frame image to obtain a same boundary image between the edge image of the background image and the edge image of the current frame image; counting a first pixel number in the edge image of the background image and a second pixel number in the same edge image; determining whether the current frame image is interfered according to a ratio of the first pixel number to the second pixel number.

Abstract: A similar drawing search device according to an embodiment configured to search for a drawing similar to a target drawing from a drawing database that stores feature information on a shape of a component in each drawing and drawing information on the component in the drawing in association with each other for a plurality of drawings. The similar drawing search device configured to acquire, from the target drawing, feature information related to a shape of a component in the target drawing; acquire, from the target drawing, drawing information on the component in the target drawing; search the drawing database for a plurality of first similar drawings, based on the feature information of the target drawing; narrow down the plurality of first similar drawings to a plurality of second similar drawings, based on the drawing information of the target drawing; and display the plurality of second similar drawings.

Abstract: Image dewarping includes capturing a source image from a camera, selecting an input row of pixels from the source image, if the input row of pixels comprises a plurality of input pixels in a region of interest in the source image, storing the plurality of input pixels to a memory to generate an input segment of pixels, when a plurality of pixels required to generate an output row of pixels are all stored in the memory, reading from the memory the plurality of pixels corresponding to the output row of pixels, and performing coordinate transformation on the plurality of pixels to generate the output row of pixels, and when coordinate transformation has been completed on the plurality of pixels, releasing from the memory an input segment of pixels of the plurality of input segments of pixels that does not correspond to other output rows of pixels.