Abstract: System and method for determining physiological parameters of a person are disclosed. A physiological parameter may be obtained by analyzing a facial image of a person, and determining, from the facial image, a physiological parameter of the person by processing the facial image with a data processor. A neural network model such as regression deep learning convolutional neural network is used to predict the physiological parameter. An image processor screens out images which can't be recognized as facial images and adjust facial images to frontal facial images for predicting of physiological parameters.

Abstract: Systems, apparatuses, and methods may provide for technology to process multi-resolution images by identifying pixels at a boundary between pixels of different resolutions, and selectively smoothing the identified pixels.

Abstract: The present invention relates to a communication technique, which is a convergence of IoT technology and 5G communication system for supporting higher data transmission rate beyond 4G system, and a system for same. The present invention can be applied to smart services (e.g. smart homes, smart buildings, smart cities, smart cars or connected cars, health care, digital education, retail businesses, security- and safety-related services and the like) on the basis of 5G communication technology and IoT-related technology.

Abstract: A system, method, and non-transitory computer readable medium are provided for training and applying defect classifiers in wafers having deeply stacked layers. In use, a plurality of images generated by an inspection system for a location of a defect detected on a wafer by the inspection system are acquired. The location on the wafer is comprised of a plurality of stacked layers, and each image of the plurality of images is generated by the inspection system at the location using a different focus setting. Further, a classification of the defect is determined, utilizing the plurality of images.

Abstract: A method for processing image array data is provided, which may include the following steps: providing the image array data detected by a sensor at a first time point and including a plurality of first blocks, and each of the first blocks has a color table corresponding thereto; segmenting the image array data detected by a sensor at a second time point into a plurality of second blocks; comparing the image array data of each first block with the image array data of each second block to generate numerical difference information; and respectively allocating the color tables corresponding to the first blocks to the second blocks matching the first blocks according to the numerical difference information.

Abstract: Systems and methods for predicting pest susceptibility, comprising steps to receive geocoded geospatial image data of a crop field from sensors, receive microclimate data of the crop field, determine a crop vigor map for the crop field, and then generate a pest susceptibility map utilizing a risk model based on the crop vigor map and the microclimate data. The pest susceptibility map comprises a measure of a susceptibility of a crop in the crop field to one or more crop pests at one or more locations. In some embodiments, the method also comprises steps to generate a treatment plan (e.g., pesticide application) and to estimate an anticipated return on investment (ROI). The system therefore leverages remote-sensed data, machine data, analytics, and machine learning to enable farmers to predict, prevent, and control the outbreak of crop pests to greatest economic effect. Such a system addresses a fundamental problem in agriculture.

Abstract: Disclosed is a portable 3-dimensional (3D) document scanning device and method. The portable 3D document scanning device includes a projector projecting light of a predetermined pattern onto a document, a 3D scanning camera capturing a pattern of the light projected onto the document and the document, and a control unit estimating a size of the captured document based on image data of the captured document, estimating a shape of the captured document based on the pattern of the projected light and the captured pattern of the light, and correcting the image data of the captured document based on the estimated size and the estimated shape.

Abstract: A system and method for generate a mood log based on user images. In one embodiment, a system includes an image module that receives images taken by a user's mobile computing device and determines that a face of the user is included in the image, a mood module that determines a mood level of the user based on the face, and a log module that stores the mood level in a log of mood levels for the user.

Abstract: The present invention relates to a contactless fingerprint recognition method using a smartphone and, more particularly, to a contactless fingerprint recognition method using a smartphone, which can generate an optimal fingerprint image without distortion regardless of various standards of built-in camera lenses of smartphones, has compatibility with a fingerprint image of a conventional optical fingerprint recognition device that has been widely popularized, and enables the fingerprint image to be converted into an image that meets the requirements of the international standard (ISO19794-4) and into optimal recognized fingerprint data (ISO19794-2), so that the utilization of contactless fingerprint recognition is further improved.

Abstract: An apparatus and method for detection of moving objects in a sequence of frames, includes circuitry, a memory, and an image-capture device. The circuitry derives a first optical flow map based on motion information of a first frame and a second frame of a plurality of frames. A second optical flow map is further derived, based on motion information of the second frame and a third frame of the plurality of frames. A first foreground region is further identified that corresponds to the moving objects across the first frame and the second frame and the identified first foreground region is warped across the first frame and the second frame and the moving objects are detected, based on combination of a plurality of pixels in the warped first foreground region and the second foreground region.

Abstract: Systems and methods for real-time user verification in online education are disclosed. In certain example embodiments, user identifying information associated with a user and a request to access online education content may be received from a user device. A face template including historical facial image data for the user can be identified. Current facial image data can be compared to the face template to determine if a match exists. Biometric sensor data, such as heart rate data, may also be received for the user. The biometric sensor data may be evaluated to determine if the user is currently located at the user device. If the user is currently located at the user device and the current facial image data matches the face template, access to the online education content may be provided to the user at the user device.

Abstract: Implementations disclosed herein include an image capture device, a system, and a method for performing multiscale denoising of an image. An image processor of the image capture device obtains a first image. The first image may be in any format and may include noise artifacts. The image processor decomposes the first image into one or more sub-images. The sub-images may range from a coarse scale to a fine scale. In some implementations, the image processor iteratively denoises each of the one or more sub-images from the coarse scale to the fine scale. The image processor reconstructs the one or more denoised sub-images to produce a denoised image. A memory of the image capture device may be configured to store the denoised image.

Abstract: A mobile cleaning robot includes a cleaning head configured to clean a floor surface in an environment, and at least one camera having a field of view that extends above the floor surface. The at least one camera is configured to capture images that include portions of the environment above the floor surface. The robot includes a recognition module is configured to recognize objects in the environment based on the images captured by the at least one camera, in which the recognition module is trained at least in part using the images captured by the at least one camera. The robot includes a storage device is configured to store a map of the environment. The robot includes a control module configured to control the mobile cleaning robot to navigate in the environment using the map and operate the cleaning head to perform cleaning tasks taking into account of the objects recognized by the recognition module.

Abstract: Systems and methods directed toward combining visible light and infrared images can include processing visible light image data to determine an edge factor value for a plurality of visible light pixels corresponding to the strength of an edge at that location. The edge factor value can be determined using features from the visible light image data and an edge gain input, which may be adjustable by a user. The edge factor values are combined with an edge midscale value to create a first set of modified visible light image data including pixels emphasized based on the strength of the edge in the visible light image. The modified visible light image data is combined with infrared image data to create combined image data having contribution from the infrared image data and the edge factor values from the visible light image data.

Abstract: Embodiments of the invention provide a method for scene understanding based on a sequence of image frames. The method comprises converting each pixel of each image frame to neural spikes, and extracting features from the sequence of image frames by processing neural spikes corresponding to pixels of the sequence of image frames. The method further comprises encoding the extracted features as neural spikes, and classifying the extracted features.

Abstract: An image recognition device includes an image acquisition unit, a moving object detection unit, and a pedestrian detection unit. The image acquisition unit acquires consecutive captured images of a surrounding of a vehicle from a camera mounted to the vehicle. The moving object detection unit calculates a moving amount based on consecutive captured images in time series acquired by the image acquisition unit to detect a moving object from the captured images. The pedestrian detection unit detects a pedestrian using an identifier for identifying a pedestrian from the captured images acquired by the image acquisition unit. The pedestrian detection unit relaxes a detection criterion for detecting a pedestrian using the identifier in a region of a captured image where the moving object is detected.

Abstract: A computer-implemented method for determining an architectural layout. The method comprises providing a cycle of points that represents a planar cross section of a cycle of walls, and, assigned to each respective point, a respective first datum that represents a direction normal to the cycle of points at the respective point. The method also comprises minimizing a Markov Random Field energy thereby assigning, to each respective point, a respective one of the set of second data. The method also comprises identifying maximal sets of consecutive points to which a same second datum is assigned, and a cycle of vertices bounding a cycle of segments which represents the architectural layout. Such a method constitutes an improved solution for determining an architectural layout.

Abstract: A system for manipulating images according to styles chosen by a user includes a feed-forward image manipulation model for everyday use and an optimization image manipulation model for more professional use. The optimization image manipulation model optimizes directly over output image pixels to minimize both the content loss and style loss. Users can select their own content and style images, and can choose between using the feed-forward image manipulation model and optimization image manipulation model.

Abstract: Disclosed herein are methods and systems for detection and discrimination of optical signals from a densely packed substrate. These have broad applications for biomolecule detection near or below the diffraction limit of optical systems, including in improving the efficiency and accuracy of polynucleotide sequencing applications.

Abstract: A method for performing inspection of a manufactured article. The method comprises acquiring a sequence of radiographic images of the article; determining a position of the article for each one of the acquired radiographic images; and performing a three-dimensional model correction loop which comprises, iteratively: generating a simulated radiographic image for each determined position of the article; and comparing the simulated radiographic images and the acquired radiographic images and generating a match result. If the match result is indicative of a mismatch, the method includes identifying and characterizing differences between the simulated radiographic images and the acquired radiographic images; correcting one of a geometry and a material density of a region of interest of the detailed three-dimensional model of the article based on each one of the identified and characterized differences; and performing a new iteration. A system for performing inspection is also provided.