Abstract: A real-time reverse image searching for images analogous to a representative frame having patterns, including identifying, on a computing device connected to a network, one of the images as the representative frame as input; providing a processor connected to the network and having access to at least one database comprising vectors associated with respective images and videos, the processor: calculating representations for the patterns in the representative frame to form a representative vector, the representations corresponding to dimensions of the vector; reducing the vector by reducing a number of the dimensions by more than 90% and a maximum trade-off between the quality of the image and the size of vector; detecting, in the at least one database, the vectors most similar to the vector of the representative frame; and offering, in real-time via the network, images and videos associated with the selected vectors. The patterns consist of colors.

Abstract: A computer-implemented method for selecting aerial images for image processing to identify Energy Infrastructure (EI) features is provided. The method includes performing image processing on aerial images of a portion of global terrain captured at different times to determine differences in terrain content the captured images. Aerial images are selected for further image processing according to identified differences in terrain content. The selected images are imaged processed via an EI feature recognition type to identify EI features within the images.

Abstract: Certain embodiments of the present disclosure relate to a computer-implemented method and system which include patch-wise coregistration (PWCR) for change detection using remote sensing images which can be taken from satellites, aircraft, UAV and other platforms, where the images can be nadir or off-nadir images and can be acquired from the same or different view-angles. The remote sensing images can be bi-temporal or multi-temporal. VHF satellite images can be used.

Abstract: The present disclosure relates to a worn banknote identification method and an ATM (Automated Teller Machine) using the same, and more particularly, to a worn banknote identification method which acquires an image of a banknote inserted into an ATM, divides pixels of the acquired banknote image into a bright region and dark region depending on a brightness distribution of the banknote image, determines the wear level of the banknote by comparing a difference between the average brightness values of the two regions to a preset reference value, and separately stores the inserted banknote into a reject box depending on the wear level of the banknote, and an ATM using the same.

Abstract: An apparatus comprises a detector and a processor. The processor may be configured to perform a two-stage object detection process utilizing the detector circuit. The detector circuit may be configured to implement a simple detection stage and a complex detection stage. In the simple detection stage, the two-stage object detection process comprises applying a first detector over a predefined region of interest. In the complex detection stage, the two-stage object detection process comprises applying a second detector on a set of best candidates identified by the simple detection stage.

Abstract: Systems and methods for detecting and classifying objects that are proximate to an autonomous vehicle can include receiving, by one or more computing devices, LIDAR data from one or more LIDAR sensors configured to transmit ranging signals relative to an autonomous vehicle, generating, by the one or more computing devices, a data matrix comprising a plurality of data channels based at least in part on the LIDAR data, and inputting the data matrix to a machine-learned model. A class prediction for each of one or more different portions of the data matrix and/or a properties estimation associated with each class prediction generated for the data matrix can be received as an output of the machine-learned model. One or more object segments can be generated based at least in part on the class predictions and properties estimations. The one or more object segments can be provided to an object classification and tracking application.

Abstract: A mobile device to provide a medical image based distortion correction mechanism is described. An image analysis application, executed by the mobile device, captures a digital copy of the medical image with a camera component in response to a user action. Distortion(s) associated with the digital copy are identified by processing the digital copy with deep neural network (DNN) model(s). Next, a manual correction description is determined to correct the distortion(s) in relation to the camera component and the medical image. Furthermore, a notification to recapture the digital copy is provided to the user. The notification includes the manual correction description. Additionally, in response to another user action to correct the distortion(s) or a failure to detect the user execute manual correction(s) associated with the distortion(s) within a time period, the distortion(s) within the digital copy are corrected and the corrected digital copy is provided to the user.

Abstract: Provided is a technology for recognizing vehicle license plate information which includes detecting a position of a license plate from a vehicle image obtained by imaging a vehicle, extracting individual character images by separating a plurality of characters from a region of the detected license plate in the vehicle image and extracting a license plate type of the license plate according to a predetermined criterion, recognizing a license plate character string on the basis of the extracted individual character images and the license plate type and outputting the recognized license plate character string.

Abstract: A system for generating and detecting watermarks within a video frame (e.g., video content) is described to determine whether a data interruption has occurred. In one or more implementations, the system includes a generation module communicatively coupled to a video source and a watermark detection module configured to receive a plurality of video watermarks. The watermarking detection module is configured to determine whether a watermark embedded in a current (e.g., a second) video frame is different from a watermark embedded in the previous (e.g., a first) video frame. The watermarking detection module is configured to generate an error signal when the watermark embedded in the current (e.g., a second) video frame is not different than the watermark embedded in the previous (e.g., a first) video frame to indicate a data interruption event has occurred.

Abstract: Apparatuses, systems and methods are provided for vehicle operator gesture recognition and transmission of related gesture data. More particularly, apparatuses, systems and methods are provided for vehicle operator gesture recognition and transmission of related gesture data based on classification of image data.

Abstract: A captured image and corresponding observed pose data are captured or received. The captured image is captured by an image capturing device onboard a vehicle. The observed pose data is determined by a location sensor onboard the vehicle. The observed pose data indicates the pose of the vehicle when the image was captured. A map projection is generated based on map data and the observed pose data. The captured image and the map projection are analyzed by a pose metric network. The pose metric network determines a pose metric based on the analysis of the captured image and the map projection. The pose metric describes how similar the captured image is to the map projection.

Abstract: A system and method includes reception of an indication of a region of interest of a plurality of image frames, determination of a first set of pixel locations of the region of interest which depict blood vessels, determination of a second set of pixel locations of the region of interest which depict non-vessel tissue, determination, for each of the plurality of the image frames, of a first contrast medium concentration corresponding to the first set of pixel locations, determination, for each of the plurality of the image frames, of a second contrast medium concentration corresponding to the second set of pixel locations, and display of a visualization depicting a first contrast medium concentration and a second medium concentration with respect to the respective time of each of the plurality of the image frames.

Abstract: A computer-implemented method comprises generating a description of a character symbol from a binarized image; comparing a template for the character symbol with the description of the character symbol based on a reference description, wherein the template comprises a grid of cells, a set of local features which may be present in the grid of cells, the reference description specifying which member of the set of local features should be present or absent in the grid of cells, and a threshold of an accepted deviation with the description of the character symbol; assigning a penalty value to the description of the character symbol via a cost function when a discrepancy exists based on the comparing; selecting the template as a match candidate for the character symbol when the penalty value is below the threshold; recognizing the character symbol based on the selecting.

Abstract: Systems and techniques for computer vision and sensor assisted contamination tracking are described herein. It may be identified that a food item has moved to a monitored area using computer vision. Sensor readings may be obtained from a sensor array. A contamination of the food item may be determined using the sensor readings. The contamination of the food item may be associated with a contamination area in the monitored area using the computer vision. A notification may be output for display in the contamination area indicating the contamination.

Abstract: Provided is a method and a system for detecting and segmenting primary video objects with neighborhood reversibility, including: dividing each video frame of a video into super pixel blocks; representing each super pixel block with visual features; constructing and training a deep neural network to predict the initial foreground value for each super pixel block in the spatial domain; constructing a neighborhood reversible matrix and transmitting the initial foreground value, constructing an iterative optimization problem and resolving the final foreground value in the temporal spatial domain; performing pixel level transformation on the final foreground value; optimizing the final foreground value for the pixel using morphological smoothing operations; determining whether the pixel belongs to the primary video objects according to the final foreground value.

Abstract: A video processing apparatus includes a video analyzer that analyzes video data captured by a surveillance camera, detects an event belonging to a specific category, and outputs a detection result, a display controller that displays, together with a video of the video data, a category setting screen for setting a category of an event included in the video, and a learning data accumulator that accumulates, as learning data together with the video data, category information set in accordance with an operation by an operator to the category setting screen. The video analyzer performs learning processing by using the learning data accumulated in the learning data accumulator.

Abstract: Disclosed herein are an apparatus and method for recognizing a posture based on a distributed fusion filter. The apparatus for recognizing a posture based on a distributed fusion filter includes a calculation unit for generating first position information about a joint of a user by receiving measurement signals from multiple inertial sensors placed on a body of the user, a recognition unit for generating second position information using output information acquired in such a way that a vision sensor captures an image of the user, and a fusion unit for fusing the first position information with the second position information and generating final position information about the joint of the user using the fused information.

Abstract: A method of image processing of magnetic resonance (MR) images for creating de-noised MR images, comprises the steps of providing image data sets including multiple complex MR images (S7), subjecting the MR images to a wavelet decomposition (S12) for creating coefficient data sets of wavelet coefficients (Sn,m) representing the MR images in a wavelet frequency domain, calculating normalized coefficient data sets of wavelet coefficients Formula (I) (S17), wherein the coefficient data sets are normalized with a quantitative amount of variation, in particular standard deviation Formula (II), of noise contributions included in the coefficient data sets (Sn,m), averaging the wavelet coefficients of each coefficient data set (S18) for providing averaged wavelet coefficients Formula (III) of the coefficient data sets, calculating phase difference maps (??n,m) for all coefficient data sets (S20), wherein the phase difference maps provide phase differences between the phase of each wavelet coefficient and the phase of

Abstract: A real-time reverse image searching for images analogous to a frame having patterns, performed using a processor connected to a network and having access to digital libraries warehousing a plurality of vectors and respective images/videos associated with each of the plurality of vectors, including: calculating representations for each of the patterns in the frame to form a vector, the representations corresponding to dimensions of the vector; reducing a size of the vector by reducing a number of the dimensions to one of about 8% and a maximum trade-off between the quality of the image and the size of vector; detecting, in the digital libraries, of the plurality of vectors that are most similar to the vector of the frame; and offering, in real-time via the network, images/videos associated with the selected of the plurality of vectors, wherein a number of the offered images and videos is pre-determined.

Abstract: A machine intelligent communication and control system is able to dynamically predict and adapt information presented to various users. The system provides a personalized experience with its ability to identify users, become contextually aware of the user's location and environment, identify objects and actions, and present customized information tailored for the user and the current environment. The system is further able to control connected items within the environment based upon various user preference considerations.