Abstract: A computer-implemented method of determining the location of a mobile device comprising a camera. The method comprises the steps of capturing, using the camera, a sequence of images over a period of time; for pairs of consecutive images from the sequence of images, determining, using a first neural network, features indicative of the motion of the device between the time the first image of the pair of images was captured and the time the second image of the pair of images was captured; for a sequence of consecutive images, determining, using a second neural network, features indicative of the location of the device from the features determined by the first neural network; and for a sequence of consecutive images, determining the location of the device from the features determined by the second neural network.

Abstract: Methods and systems for real time localization of a device using image data are disclosed herein. A disclosed method for localizing a device with respect to a known object includes capturing an image of at least a portion of the known object. The method also includes determining, using a trained machine intelligence system and the image, a set of known object coordinates for a set of known object pixels of the image. The set of known object coordinates: are outputs of the trained machine intelligence system; are in a frame of reference of the object; and encode each object coordinate in the set of known object coordinates using an encoding with at least two values per object coordinate. The method also includes localizing the device with respect to the known object using the set of known object coordinates from the trained machine intelligence system.

Abstract: Methods, systems and computer readable media for computerized modeling of a subject (e.g., a human body) are described.

Abstract: Provided are a medical image analyzing system and a method thereof, which mainly crop a plurality of image patches from a processed image including a segmentation label corresponding to a location of an organ, train a deep learning model with the image patches to obtain prediction values, and plot a receiver operating characteristic curve to determine a threshold which determines whether the image patches are cancerous, thereby effectively improving the detection rate of cancer.

Abstract: A system for processing breast tissue images includes an image processing computer and a user interface operatively coupled to the image processing computer, wherein the image processing computer is configured to obtain image data of breast tissue, processing the image data to generate a set of reconstructed image slices, the reconstructed image slices collectively depicting the breast tissue, process respective subsets of the reconstructed image slices to generate a set of image slabs, each image slab comprising a synthesized 2D image of a portion of the breast tissue obtained from a respective subset of the set of reconstructed image slices.

Abstract: A position determination apparatus for determining, from a first image that is an image including at least a desired first subject, a position of the desired first subject, includes: a feature amount acquisition unit that acquires a first feature amount representing a predetermined feature of the first image; an estimation unit in which a second feature amount representing the predetermined feature obtained from a second image including a second subject is associated with a selected feature map that is a feature map corresponding to the second subject among a plurality of feature maps that are a set of feature maps that are maps representing features of the second image; an estimated first feature map that is estimated by the estimation unit to be associated with the first feature amount: and a position determination unit that determines the position of the desired first subject using the estimated first feature map.

Abstract: A method and device for blurring an image background, a storage medium, and an electronic apparatus. The method for blurring an image background comprises: using a preset classification model to divide an image to be processed into a foreground region and a background region (201); detecting a contour edge of a photographic subject in the foreground region obtained from the division (S202); and performing blurring on a background of the image according to the contour edge of the photographic subject (S203).

Abstract: An example apparatus for processing images includes a trainable vision scaler to receive an image. The trainable vision scaler is to generate output including a feature map or an enhanced image based on the image. The trainable vision scaler is to transmit the output to a computer vision network. The computer vision network is trained to perform a computer vision task using the output.

Abstract: Systems and methods for synthetic medical image generation in accordance with embodiments of the invention are illustrated. One embodiment includes a synthetic medical image generation system, including a processor, and a memory containing an image synthesis application, where the image synthesis application directs the processor to obtain source image data generated by at least one medical imaging device, where the source image data describes a functional medical image taken of a patient administered with a first imaging agent, and synthesize a predicted medical image of the patient that depicts the patient as if they were administered with a second imaging agent, wherein the first imaging agent and the second imaging agent are different imaging agents.

Abstract: Scrambling a point cloud (PC), including: receiving the PC in polar coordinates, wherein each point of the PC includes an index; scrambling each point of the PC by translating each point along a radial axis of the polar coordinates by adding a pseudo-random number (PRN) to each point, wherein the PRN is generated using the index and a secret key.

Abstract: A method for counting a number of moving objects that cross at least one predefined curve in a scene comprises making detections of positions of one or more moving objects in the scene, tracking the positions of the moving objects over time based on the detections to produce one or more corresponding tracks, wherein each track is described by a time dependent probability density function, calculating, for each moving object, a success probability pi that the moving object succeeded to cross the at least one predefined curve in the scene, wherein the success probability is calculated by using the time dependent probability density function describing the track of the moving object, and calculating an expected value and a variance of a number of moving objects that crossed the at least one predefined curve by summing success probabilities pi and summing products pi(1?pi) of success and corresponding failure probabilities, respectively.

Abstract: Signal detection and recognition employees coordinated illumination and capture of images under to facilitate extraction of a signal of interest. Pulsed illumination of different colors facilitates extraction of signals from color channels, as well as improved signal to noise ratio by combining signals of different color channels. The successive pulsing of different color illumination appears white to the user, yet facilitates signal detection, even for lower cost monochrome sensors, as in barcode scanning and other automatic identification equipment.

Abstract: A system, method, and apparatus for displaying a fused reconstructed image with a multidimensional image are disclosed. An example imaging system receives a selection corresponding to a portion of a displayed multidimensional visualization of a surgical site. At the selected portion of the multidimensional visualization, the imaging system displays a portion of a three-dimensional image which corresponds to the selected multidimensional visualization such that the displayed portion of the at least one of the three-dimensional image or model is fused with the displayed multidimensional visualization.

Abstract: An electrophoretic separation data analyzing apparatus includes an analysis target peak identifying part configured to require a user to input analysis target peak information on analysis target peaks to be added to an analysis target in separation data obtained by electrophoretic separation, and to identify at least one of the analysis target peaks based on the analysis target peak information, a peak-of-interest identifying part configured to require the user to input peak-of-interest information on a peak of interest among the analysis target peaks, and identify the peak of interest based on the peak-of-interest information, and an abundance ratio calculating part configured to determine an abundance ratio of the peak of interest among all of the analysis target peaks based on a total value of peak areas of the analysis target peaks and a peak area value of the peak of interest.

Abstract: The present description relates to light patterns used in a live action scene of a visual production to encode information associated with objects in the scene, such as movement and position of the objects. A data capture system includes active markers that emit light of a particular wavelength in predefined strobing patterns. In some implementations, the active markers are instructed to emit an assigned signature pattern of light through a signal controller sending signals to a control unit. Various components are synchronized such that pulsing of light corresponds to time slices and particular frames captured by the performance capture system. The data representing the pattern is embedded in illuminated and blank frames. Frames showing the light pattern are analyzed to extract information about the active markers, such as identification of the active markers and objects to which they are attached.

Abstract: A method of training a system to extract information from documents comprises feeding digital form of training documents to an OCR module, which identifies multiple logical blocks in the documents and text present in the logical blocks. One or more tags for the whole of the document, the logical blocks and word tokens on the document are received by a tagging module. A text input comprising the text identified in the document and the tags for the whole of the document are received by a machine learning module. A first image of the document with layout of the one or more of the identified blocks superimposed, and the tags of the logical blocks in the document are received by the machine learning module, wherein the received text input, first image and tags for the logical blocks corresponds to a plurality of the training documents.

Abstract: An improvement to automatic classifying of threat level of objects in CT scan images of container content, methods include automatic identification of non-classifiable threat level object images, and displaying on a display of an operator a de-cluttered image, to improve operator efficiency. The de-cluttered image includes, as subject images, the non-classifiable threat level object images. Improvement to resolution of non-classifiable threat objects includes computer-directed prompts for the operator to enter information regarding the subject image and, based on same, identifying the object type. Improvement to automatic classifying of threat levels includes incremental updating the classifying, using the determined object type and the threat level of the object type.

Abstract: The disclosure is related to a panoramic radiography device. The panoramic radiography device may include an image processor and a viewer module. The image processor may be configured to produce a primary panoramic image using a first image layer and a secondary panoramic image using a secondary image layer based on a plurality of image frame data, wherein the second image layer is different from the first image layer in at least one of a number, a position, a shape, an angle, and a thickness. The viewer module may be configured to i) provide a graphic user interface having a primary display area and a secondary display area arranged at a predetermined position of the primary display area, ii) display the primary panoramic image at the primary display area, and iii) display a part of the secondary panoramic image at the secondary display area, wherein the part of the secondary panoramic image corresponds to the predetermined position.

Abstract: A method is for detecting respective potential presence of respective different antinuclear antibody fluorescence pattern types on a biological cell substrate including human epithelioma cells, including: acquiring a first image which represents staining of the cell substrate by a first fluorescent dye, and acquiring a second image which represents staining of the cell substrate by a second fluorescent dye, detecting, on the basis of the first image, respective image segments which in each case represent at least one mitotic cell, selecting, on the basis of the detected image segments, subimages of the first image and subimages corresponding thereto of the second image and detecting, on the basis of the selected subimages of the first image and of the selected subimages of the second image, respective actual presence of respective cellular fluorescence pattern types by means of a convolutional neural network.

Abstract: An image segmentation method, an image segmentation apparatus, an image segmentation device are provided, the image segmentation method including: extracting, from a current frame of a video image, a skeleton two-dimensional estimation and a skeleton three-dimensional estimation of a human three-dimensional skeleton; obtaining a target three-dimensional skeleton based on the skeleton two-dimensional estimation and the skeleton three-dimensional estimation; implementing image segmentation based on the target three-dimensional skeleton; wherein the human three-dimensional skeleton has multiple nodes, and the video image is a two-dimensional image, when calculating the target three-dimensional skeleton in the current frame, by comprehensively considering the skeleton two-dimensional estimation and skeleton three-dimensional skeleton estimation of the human three-dimensional skeleton in the current frame, the accuracy and robustness of the obtained target three-dimensional skeleton can be improved, thereby improv