Abstract: According to an embodiment, an image analyzer includes a set unit, a first calculator, a second calculator, a divider, a third calculator, and a specifier. The set unit sets multiple partial regions in the image. The first calculator calculates an optical flow in a partial region. The second calculator calculates the density of an object included in the partial region. The divider divides the image into the multiple blocks. The third calculator calculates, for a block, a statistical amount that is derived from the density and the moving amount of the object derived from the optical flow for the partial region included in the block. The specifier specifies the block, out of the blocks, as an unsteady block that is in an unsteady state on the basis of the statistical amount.

Abstract: One or more embodiments of an image enhancement system enable a computing device to generate an enhanced digital image. In particular, a computing device can enhance a digital image including, for example, a photograph of a whiteboard, document, chalkboard, or other object having a uniform background. The computing device can determine modifications to apply to the digital image by minimizing an energy heuristic that both causes pixels of the digital image to change to a uniform color (e.g., white) and preserves gradients from the digital image. The computing device can further generate an enhanced digital image by applying the determined modifications to the digital image.

Abstract: A method, an apparatus and a system for recognizing an evaluation element are provided. The method includes receiving an input text; performing, using a first conditional random field model, first recognition for the input text to obtain a first recognition result, the first recognition result including a pre-evaluation element that is recognized by using the first conditional random field model; performing, using a second conditional random field model, second recognition for the input text to obtain a second recognition result, the second recognition result including a false positive evaluation element that is recognized by using the second conditional random field model, the false positive evaluation element being an element erroneously detected as an evaluation element; and recognizing, based on the first recognition result and the second recognition result, an evaluation element in the input text.

Abstract: A dynamic diagnosis support information generation system includes: a radiation generator capable of irradiating a pulsed radiation; a radiation detector which is provided with a plurality of detecting elements arranged in two-dimension, detects the pulsed radiation irradiated from the radiation generator at each of the plurality of detecting elements and generates frame images successively; and an analysis section which calculates and outputs a feature value relating to a dynamic image of a subject based on a plurality of frame images generated by radiographing the subject by using the radiation generator and the radiation detector, wherein the analysis section calculates the feature value relating to the dynamic image of the subject by corresponding pixels to each others representing outputs of a detecting element at a same position in the radiation detector among the plurality of the frame images.

Abstract: A device configured to emulate an image output adapter for a correlithm object processing system that includes an actor engine. The actor engine is configured to receive an aggregated correlithm object corresponding with a mask and to identify a plurality of correlithm objects in the aggregated correlithm object. Each mask table is linked with a mask that defines an array of pixels of an image. The actor engine is configured to populate each pixel location in the mask with a correlithm object from the plurality of correlithm object in accordance with a mask table for the mask. The actor engine is further configured to determine a pixel value for each pixel location in the mask based on the correlithm object at each pixel location and to output a representation of a portion of the image based on the mask populated with pixel values at each pixel location.

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: Devices and systems for image-based analysis of test media are disclosed herein. An example device includes four side panels connected together so as to form a tubular rectangle, a floor panel that covers an opening of the tubular rectangle, the floor panel having a raised test bed that receives a test medium, a top panel that having an optical lens that aligns with the raised test bed when the top panel covers another opening of the tubular rectangle. The optical lens is aligned with an aperture that extends through the top panel. The four side panels, the floor panel, and the top panel forming an optic chamber when joined together. The device also includes a light source that illuminates inside the device.

Abstract: A system that automatically manages a collateral risk and a business performance of an entity is provided. The system generates a customizable database to store critical accounting and ancillary business information. The system automatically updates the customized database at predefined time periods based on new accounting and ancillary business information. The system automatically enables the customized database for scalable assessment of a collateral risk and a business performance of an entity. The system determines the collateral risk and business performance of an entity and provides the collateral risk, and business performance of the entity and an analytical summary of the accounting and the ancillary business information to a machine learning model. The system recommends actions to be performed to reduce the collateral risk and to improve the business performance based on the accounting and ancillary business information.

Abstract: An image-processing method of removing noise from an image includes: obtaining standard representative values for standard regions of a standard image and reference representative values for reference regions of a reference image, and obtaining a plurality of hierarchical images having different resolutions with respect to the standard image and the reference image based on the standard representative values and the reference representative values; obtaining the standard representative values for the standard regions of the standard image and the reference representative values for the reference regions of the reference image from the hierarchical images; determining a similarity between the standard regions and the reference regions from the standard representative values and the reference representative values; and removing noise by applying filtering to the standard image and the reference image depending on the determined similarity.

Abstract: A system and method for segmenting a current frame of a video includes receiving a segmentation mask determined from a previous frame of the video, receiving a background model value and a background deviation value for a given pixel of a previous frame of the video, updating the received background deviation value, updating the background model value independently of the updating of the background deviation value and determining a value of a pixel of a new segmentation mask corresponding to the given pixel based on a foreground model value of the current frame, a segmenting background model value of the current frame and a segmentation threshold, the determining of the new segmentation mask defining whether the given pixel is a foreground pixel or a background pixel of the current frame. The segmentation mask is used for detecting objects, classifying objects and detecting events in the scene captured by the camera.

Abstract: Techniques related to improved video frame segmentation based on color, motion, and texture are discussed. Such techniques may include segmenting a video frame of a video sequence based on only dominant color when the frame does not have a dominant motion nor a global motion in a high probability region of dominant color within the video frame.

Abstract: A method for providing a content based on a user's preference(s) includes analyzing meta-data information of a pre-stored content, determining at least one preference based on the analyzed meta-data information, transmitting the at least one preference to a content-providing server; searching, at the content-providing server, for at least one content corresponding to the at least one preference, extracting general information of at least one content found to correspond to the at least one preference and transmit the general information to the portable terminal.

Abstract: A method for assessing the presence and/or the severity of a lesion in an organ or tissue of a subject through automated analysis of at least one image of the organ or tissue is provided. In particular, the organ or tissue is a liver organ or liver tissue. The method includes the calculation of a score that combines descriptors of the image, and includes the steps of: a) measuring on the image at least two descriptors of the image, b) mathematically combining the descriptors in a score; and c) assessing the presence and/or the severity of a lesion in the organ or tissue based on the value of the score calculated at step b).

Abstract: Embodiments of this disclosure belong to the field of computer technologies and disclose a method and an apparatus for recognizing a character string in an image.

Abstract: Disclosed are various embodiments to extract portions of video or audio data from a media summary corresponding to a media content item available in a media content catalog according to one or more predefined rules. The extracted portions of video and audio data are used to generate one or more network pages detailing or describing the media content item.

Abstract: An apparatus includes a mode determination circuit configured to determine an input mode from at least a first mode and a second mode; an input circuit configured to receive a signal based on a user input; and an image processing circuit configured to determine a subset of an image including a desired image area based on the user input of a first line in the first mode, and to determine the desired image area based on the user input of a second line on the subset of the image in the second mode.

Abstract: The present invention provides a pixel drive circuit, wherein the pixel drive circuit comprises a plurality of cascading pixel drive units, and each pixel drive units comprising: a first resetting circuit is connected to a first pixel for receiving an input voltage and resetting the first pixel; a second resetting circuit is connected to a second pixel for receiving an input voltage and resetting the second pixel; a first controlling circuit is connected to the first and the second resetting circuits for receiving a reference voltage and supplying the reference voltage to the first and second resetting circuits; and a second controlling circuit is connected to the first and the second resetting circuits for receiving data voltages and supplying the data voltages to the first and the second resetting circuits to drive the first and the second pixels simultaneously.

Abstract: Presented herein are techniques for automatically generating object segmentation training data. In particular, a segmentation data generation system is configured to obtain training images derived from a scene captured by one or more image capture devices. Each training image is a still image that includes a foreground object and a background. The segmentation data generation system automatically generates a mask of the training image to delineate the object from the background and, based on the mask automatically generates a masked image. The masked image includes only the object present in the training image. The segmentation data generation system composites the masked image with an image of an environmental scene to generate a composite image that includes the masked image and the environmental scene.

Abstract: A context aware clipping mask is described. Context aware clipping masks may provide an automated approach for creating clipping sets that generate aesthetically pleasing photo texts. In at least some implementations, an input image is analyzed to generate an image saliency map and an image gradient map. A plurality of image rects of varying sizes and aspect ratios are generated on a grid over the input image. A score is assigned to each image rect, incorporating a visual composition, a boundary simplicity based on the image gradient map, and a content preservation based on the image saliency map. An image rect with the highest score is selected and utilized to create a photo text from the input image.

Abstract: Methods and apparatus provide for: capturing an image of an object, which includes a face of a person wearing an optical display apparatus by which to observe a stereoscopic image that contains a first parallax image and a second parallax image obtained when the object in a three-dimensional (3D) space is viewed from different viewpoints; identifying the optical display apparatus included in the image of the object; and generating an image of the face of the person that does not include the optical display apparatus by excluding the identified optical display apparatus, and instead by adding features of the face of the person to a region in which the identified optical display apparatus is excluded.

Abstract: This disclosure provides systems and methods to automatically classify stent struts as covered or uncovered and to measure the thickness of tissue coverage. As one example, the method includes storing three-dimensional image data acquired intravascularly via an optical coherence tomography (OCT) apparatus and detecting struts based on analysis of the image data. Image data corresponding to each of the detected struts is further analyzed automatically to compute an indication of tissue coverage for the stent.

Abstract: A device for segmenting an image of a subject (36), includes a data interface for receiving an image of the subject (36), which image depicts a structure of said subject (36). A translation unit translates a user-initiated motion of an image positioner into a first contour (38) surrounding said structure. A motion parameter registering unit registers a motion parameter of said user-initiated motion to said first contour (38). The motion parameter includes a speed and/or an acceleration of an image positioner. An image control point unit distributes a plurality of image control points (40) on the first contour with a density decreasing with the motion parameter. A segmentation unit segments the image by determining a second contour (44) within the first contour based on the plurality of image control points (40). The segmentation unit is configured to use one or more segmentation functions.

Abstract: A waste management system and associated method are used to control routing of an autonomous waste receptacle in a facility. The autonomous waste receptacle includes a cavity for storing trash, a trash level sensor for sensing a level of trash stored therein, and a motor operative to move the waste receptacle. Position trackers sense positions of the autonomous waste receptacle and of patrons in the facility. Additionally, concession consumption concession consumption data indicative of sales performed by concessions in the facility are stored. A processing subsystem controls the waste receptacle to move autonomously in the facility along a route determined according to correlations between concession consumption data, trash levels monitored by the waste receptacle, and patron positions.

Abstract: Techniques, systems, and devices are disclosed for analyzing a point of closest approach (PoCA) image of a volume of interest (VOI) comprising a set of recorded PoCA points from charged particle detector measurements to detect an object within the VOI. The VOI is partitioned into a set of equally-sized bins with each bin including a subset of the PoCA points. A bin metric is determined for each bin. A subset of the bins is selected based on the detected bin metric with the subset of bins being most likely to contain objects. A potential object for each selected bin is determined by determining a location and a size for the potential object based at least on the PoCAs inside the bin. A figure of merit (FOM) of the potential object is determined as a measure of the likelihood that the potential object is truly a threat object.

Abstract: Systems and methods for transmitting and receiving image data captured by an imager array including a plurality of focal planes are described. One embodiment of the invention includes capturing image data using a plurality of active focal planes in a camera module, where an image is formed on each active focal plane by a separate lens stack, generating lines of image data by interleaving the image data captured by the plurality of active focal planes, and transmitting the lines of image data and the additional data.

Abstract: Disclosed is a method and system for creating labels for cluster in computing environment. The system comprises receiving module, candidate items selector, combination array generator, coverage value analyzer, candidate pair selector, unique word filter and cluster label selector. Receiving module receives input data and candidate items selector selects candidate items occurring repetitively using n-gram technique to generate list of candidate items with frequency of occurrence. Combination array generator selects candidate items to populate two-dimensional array wherein each array element represents pair of n-gram. Coverage value analyzer determines coverage value for each pair of n-gram from array. Candidate pair selector selects pairs of n-gram from two-dimensional array to process and generate list of candidate pairs. The unique word filter determines number of unique words in each candidate pair.

Abstract: Electronic documents may be large and have numerous pages, sections and areas of information that are useful to some individuals and not others. It is common for large documents to include some information that is intended for only certain recipients and other information that is intended for other recipients. One example may provide receiving a document including a number of pages, identifying a number of extraction attributes corresponding to various users identified in the document, querying the document for the extraction attributes, and creating a number of new documents corresponding to the extraction attributes.

Abstract: Embodiments of the present invention provide techniques for coding video data efficiently based on detection of objects within video sequences. A video coder may perform object detection on the frame and when an object is detected, develop statistics of an area of the frame in which the object is located. The video coder may compare pixels adjacent to the object location to the object's statistics and may define an object region to include pixel blocks corresponding to the object's location and pixel blocks corresponding to adjacent pixels having similar statistics as the detected object. The coder may code the video frame according to a block-based compression algorithm wherein pixel blocks of the object region are coded according to coding parameters generating relatively high quality coding and pixel blocks outside the object region are coded according to coding parameters generating relatively lower quality coding.

Abstract: An image-processing device and method for foreground mask correction for object segmentation, includes receipt of a sequence of image frames. A first FG mask is estimated using depth information associated with the input image frame and by binarizing a difference between the input image frame and a background (BG) image of the input image frame. A first set of pixels with a first mask value to be updated to a second mask value is identified in a boundary region of the estimated first FG mask. A second FG mask is determined based on the identification of the first set of pixels in the boundary region of the estimated first FG mask.

Abstract: In some implementations, a computer-implemented method is capable of automatically segmenting and detecting a tattoo within an image. An image may be initially obtained. A block coverage pattern that identifies multiple blocks within the obtained image may be determined. A set of processing operations may then be performed for each block. The processing operations may include calculating a plurality of statistical features. A confidence score reflecting a likelihood that at least a portion of the block includes a predetermined graphical attribute associated with tattoos may be calculated. A subset of the multiple blocks of the image that have a respective confidence score greater than a predetermined threshold value may be identified. A portion of the image that includes one or more blocks from among the subset of the multiple blocks may then be determined to correspond to a tattoo.

Abstract: A head mountable display (HMD) includes a camera operable to capture images of a peripheral and/or control device in use by a wearer of the HMD. A detector of the HMD is configured to detect occlusions in a captured image of the peripheral and/or control device. And an image renderer of the HMD is configured to render a virtual version of the peripheral and/or control device for display to the HMD wearer and to render a representation of a user's hand at a position of a detected occlusion.

Abstract: Described is a system for object detection in images or videos using spiking neural networks. An intensity saliency map is generated from an intensity of an input image having color components using a spiking neural network. Additionally, a color saliency map is generated from a plurality of colors in the input image using a spiking neural network. An object detection model is generated by combining the intensity saliency map and multiple color saliency maps. The object detection model is used to detect multiple objects of interest in the input image.

Abstract: Disclosed is a method and system for processing images from an aerial imaging device. The method includes receiving a first image of a geographical area having a first resolution. The method transmits the first image to a machine learning model to identify an area of interest containing an object of interest. The method receives a second image of the geographical area having a second resolution higher than the first resolution. The method transmits the second image to the machine learning model to determine a likelihood that the area of interest contains the object of interest. The method trains the machine learning model to filter out features corresponding to the area of interest in images having the first resolution if the likelihood is below a threshold. The method transmits a visual representation of the object of interest to a user device if the likelihood exceeds the threshold.

Abstract: An object distance computing method, applied to an image sensor comprising a plurality of first type pixels. The first type of pixels comprises a first group and a second group of first type pixels. The method comprises: blocking a first part for each pixel for the first group of first type pixels, and blocking a second part for each pixel for the second group of first type pixels; retrieving a first image of an object via a non-blocked part of each pixel for the first group of first type pixels; retrieving a second image of an object via a non-blocked part of each pixel of the second group of first type pixels; combining the first image and the second image to generate a first combined image; and computing first distance information for the object and the image sensor according to a blur level of the first combined image.

Abstract: The invention comprises a method and apparatus for treating a tumor, comprising the steps of: (1) a main controller implementing an initial radiation treatment plan, as a current radiation treatment plan, using positively charged particles delivered from a synchrotron, along a beam transport line, through a nozzle system proximate the treatment room, and into the tumor; (2) concurrent with the step of implementing, imaging the tumor, such as with protons, to generate a current image; (3) upon detection of movement of the tumor relative to surrounding constituents of the patient using the current image, the main controller, using computer implemented code, automatically generating an updated treatment plan, the updated treatment plan becoming the current radiation treatment plan; and (4) repeating the steps of implementing, imaging, and generating an updated treatment plan at least n times, where n is a positive integer of at least one.

Abstract: A method and an electronic apparatus for image background learning are provided. In the method, a memory space for recording multiple historical background values of each pixel in an input image is disposed in a memory device, in which the memory space is divided into a lock area and an open area. Whenever receiving the input image, a processor determines whether each pixel in the input image is a background pixel according to the historical background values recorded in the memory space. If the pixel is determined as the background pixel, the processor updates one of the historic background values recorded in the open area by using the pixel value of the pixel while keeping the historical background values in the lock area unchanged. The processor also periodically switches a location of the lock area in the memory space, so as to forget old historical background values.

Abstract: Disclosed are systems and methods for detecting moving objects. A computer-implemented method for detecting moving objects comprises obtaining a streaming video captured by a camera; extracting an input image sequence including a series of images from the streaming video; tracking point features and maintaining a set of point trajectories for at least one of the series of images; measuring a likelihood for each point trajectory to determine whether it belongs to a moving object using constraints from multi-view geometry; and determining a conditional random field (CRF) on an entire frame to obtain a moving object segmentation.

Abstract: An optimization method of image depth information and an image processing apparatus are provided. A to-be-repaired depth map generated based on a left image and a right image is obtained. A superpixel segmenting process is performed on the left image or the right image to obtain multiple superpixels. A plurality of image segments are obtained by aggregating the superpixels according to pixel information in the superpixels. A hole filling process is performed on holes of the to-be-repaired depth map to obtain a hole-filled depth map. A statistical analysis is performed on first valid depth values of the to-be-repaired depth map and second valid depth values of the hole-filled depth map to obtain a plurality of optimized depth values by using the ranges of the image segments, the ranges of the superpixels, the to-be-repaired depth map, and the hole-filled depth map.

Abstract: A method of classifying a work machine within a worksite is provided. The method may include receiving one or more captured images of the work machine from one or more image capture devices, identifying at least two classifiers within the captured images of the work machine, determining spatial relationships between the classifiers within the captured images, determining a classification and a pose of the work machine based on the spatial relationships, and displaying analytics based on the classification and the pose of the work machine.

Abstract: Various embodiments herein each include at least one of systems, methods, and software for feature flow for video recognition. Such embodiments generally include a fast and accurate framework for video recognition. One example method includes receiving a first frame captured by an imaging device and designating the first frame as a key frame. The method may then generate at least one feature map to identify features in the key frame and subsequently receive a second frame. The method also includes designating the second frame as a current frame and applying a flow estimation algorithm to the key frame and current frame to generate a flow field representing a flow from the key frame to the current frame. The method then propagates each of the at least one feature maps based on the flow field to approximate current locations of features identified within each of the at least one feature maps.

Abstract: A method for deconvolution of digital images includes obtaining a degraded image from a digital sensor, a processor accepting output from the digital sensor and recognizing a distorted element within the image. The distorted element is compared with a true shape of the element to produce a degrading function. The degrading function is deconvolved from at least a portion of the image to improve image quality of the image. A method of indirectly decoding a barcode includes obtaining an image of a barcode using an optical sensor in a mobile computing device, the image comprising barcode marks and a textual character. The textual character is optically recognized and an image degrading characteristic is identified from the textual character. Compensating for the image degrading characteristic renders previously undecodable barcode marks decodable. A system for deconvolution of digital images is also included.

Abstract: An apparatus generates an image having a plurality of pixels, each of the plurality of pixels corresponding to a range point and representing a distance value, extracts from the image a first area having a plurality of range points at which the distance value is less than or equal to a first threshold wherein a difference between each pair of the plurality of range points included in the first area is less than or equal to a second threshold, and determines the first area as a noise area when the first area meets a certain condition.

Abstract: To compress a document, a number of edges present in a selected portion of the document are counted to determine whether the number of edges exceeds a threshold. When the number of edges exceeds the threshold, a pixel is selected from the portion and a set of neighboring pixels is identified for the pixel. For each neighboring pixel in a subset of the neighboring pixels, a corresponding label of the neighboring pixel is identified. A mask layer contains labels of pixels in the portion where a label of the selected pixel is biased using labels of neighboring pixels in the subset of the neighboring pixels. The selected pixel is designated to a foreground or a background layer of the document according to the label of the selected pixel. A compressed document is constructed corresponding to the document using the mask layer, the foreground layer, and the background layer.

Abstract: Methods and apparatus to capture photographs using mobile devices are disclosed. An example apparatus includes a photograph capturing controller to capture a photograph with a mobile device. the example apparatus further includes a perspective analyzer, implemented by the mobile device, to analyze the photograph to determine a probability of perspective being present in the photograph. The example apparatus also includes a photograph capturing interface to prompt a user to capture a new photograph when the probability of perspective exceeds a threshold.

Abstract: A computer vision system and method for detecting and modeling features of a building in a plurality of images is provided. The system includes at least one computer system in communication with a database of aerial imagery, and computer vision system code executed by the at last one computer system which automatically detects contours and infers interior roof features of the building. The system first processes the plurality of images to identify a plurality of two-dimensional (2D) line segments in each image. Then, the system processes the plurality of 2D line segments to generate a plurality of three-dimensional (3D) line segments. The plurality of 2D line segments are then processed to detect a contour of the structure, and the contour of the structure is utilized by the system to infer interior roof lines from the structure. A model of the roof of the structure is finally generated using the detected contour and interior roof lines.

Abstract: A system, computer readable medium, and method for sub-frame scan-out are disclosed. The method includes the steps of dividing a frame into a plurality of slices. For each slice in the plurality of slices, the steps further include sampling a sensor associated with a head mounted display to generate sample data corresponding to the slice; adjusting one or more parameters associated with rendering operations for the slice based on the sample data; and rendering primitive data associated with a model according to the rendering operations to generate image data for the slice. Each slice is a portion of the frame and corresponds to different sample data from the sensor. Thus, adjusting of the parameters is different for each slice of the frame.

Abstract: An information processing device sets a second scaling factor used to display a character image extracted from an image. The second scaling factor is different from a first scaling factor used to display a background image extracted from the image. The information processing device adjusts at least either the character image changed in display size with the second scaling factor or the background image changed in display size with the first scaling factor, based on the relationship between the display state of the character image changed in display size and the display state of the surrounding area of the character image that has been changed in display size and is overlaid on the background image changed in display size.

Abstract: A method of illuminating a subject during photography is disclosed. The method includes illuminating a background lighting system during a first image capture, illuminating a subject lighting system during a second image capture, and illuminating the background lighting system during a third image capture. The time from the first image capture to the third image capture is less than about 100 milliseconds. Also disclosed is a method for generating a composite mask of a subject, including receiving the three images, determining any movements of the subject between the first and third images, estimating an intermediate position of the subject during the second image, and generating a composite mask at the estimated intermediate position.

Abstract: A method for improving the placement of virtual content in augmented reality is disclosed. A reference image of the object to be augmented is analyzed for feature density information. The placement of content is based on the at least one location adjacent to where features are concentrated. Accordingly, the chance of the content interfering with an important part of the object is lowered, and object recognition and/or tracking ability is maintained because there are sufficient features nearby the content to enable object recognition and/or tracking.

Abstract: A medical image processing device includes a port, a processor and a display. The port acquires a plurality of image data from a living body. The processor classifies the plurality of image dam to genes ate a plurality of image groups based OH a first time component. The first time component is defined by a first time interval among imaging times at which the plurality of image data are generated. The processor correlates each image data in one image groups with each image data in another image group, based on both an actual time and a time ratio of a second time component. The second time component is defined by a second time interval among the imaging times being shorter than the first time interval. The display displays images based on the plurality of image data based on the correlation of the image data in the image groups.