Abstract: A method with image processing includes: setting an offset window for an offset pattern of a kernel offset and an offset parameter for an application intensity of the kernel offset; determining an output kernel by applying the kernel offset to an input kernel based on the offset window and the offset parameter; and adjusting contrast of a degraded image using the output kernel.

Abstract: Systems and methods for image modification to increase contrast between text and non-text pixels within the image. In one embodiment, an original document image is scaled to a predetermined size for processing by a convolutional neural network. The convolutional neural network identifies a probability that each pixel in the scaled is text and generates a heat map of these probabilities. The heat map is then scaled back to the size of the original document image, and the probabilities in the heat map are used to adjust the intensities of the text and non-text pixels. For positive text, intensities of text pixels are reduced and intensities of non-text pixels are increased in order to increase the contrast of the text against the background of the image. Optical character recognition may then be performed on the contrast-adjusted image.

Abstract: Example systems and methods for lesion detection are described herein. An example system includes at least one processor and a memory operably coupled to the at least one processor. The system also includes a candidate selection module configured to receive an image, determine a plurality of candidate points in the image, and select a respective volumetric region centered by each of the candidate points. A portion of a lesion has a high probability of being determined as a candidate point. The system further includes a deep learning network configured to receive the respective volumetric regions selected by the candidate selection module, and determine a respective probability of each respective volumetric region to contain the lesion. Additionally, example methods for training a deep learning network to detect lesions are described herein.

Abstract: Described herein are embodiments for performing pattern recognition using a hierarchical network. The hierarchical network is made up of fractal cognitive computing nodes that manage their own interconnections and domains in an unsupervised manner. The fractal cognitive computing nodes are also self-replicating and may create new levels within the hierarchical network in an unsupervised manner. The form of signals processed in the hierarchical network may take on the form of key-value pairs. This may allow the hierarchical network to replicate and perform adaptive pattern recognition in non-domain-specific manner with regards to the input signals.

Abstract: A method is explained for processing an array of pixels in a point cloud. Local error bars are calculated for each pixel distance value. A difference is calculated between distance values of the pixel being processed and neighboring pixels with distance values within the error bars. If the difference is outside the error bars, the distance value of the pixel being processed is changed by a small fraction while remaining inside the error bars; if the difference is within the error bars, the pixel value is replaced by a weighted average. The neighboring pixels with distance values within the error bars of the pixel are counted and if a predetermined threshold is met, the counted values are averaged and replace the pixel value, but if not met, the pixel value is unchanged. If loop exit criteria have been met, the loop is terminated and if not, looping begins again.

Abstract: An object is to provide an image processing apparatus capable of appropriately distinguishing changes in an area that have occurred over a period of time. An image processing apparatus may include: a difference image generator means to generate a difference image from input SAR images; an intensity change feature extractor means to extract an intensity-based change feature from the difference image; a speckle change feature extractor means to extract speckle-based change features from the input SAR images; a combined feature extractor means to combine the intensity change feature and the speckle change feature to generate a complete representation of changes; and a classifier means to classify the pixels in several change classes using the combined feature and output a change map.

Abstract: The present disclosure relates to a method and apparatus for association detection for a human face and a human hand, an electronic apparatus and a storage medium. The method comprises: acquiring a first image, the first image being an image of a human object; performing feature extraction on the first image to obtain a first feature map of multiple dimensions; performing a feature fusion processing on the first feature map of multiple dimensions to obtain a second feature map of multiple dimensions, the dimensions of the second feature map corresponding to the dimensions of the first feature map in a one-to-one manner; detecting, on the basis of the obtained second feature map of multiple dimensions, a human face position and a human hand position associated with the same human object in the first image. The embodiment of the present disclosure enables easy and convenient association detection for human face and human hand.

Abstract: The system comprises of a security label engaged to a package. The label comprises of a first layer with a first code and a second layer with a second code. The first layer is disposed over the second layer in a way that at least a portion of the second code on the second layer is covered by the first layer. The second code on the second layer is revealed upon irreversibly disengaging the first layer from the package. The first code is associated with a first information and the second code is associated with a second information. The second code on the second layer is associated with the first code on the first layer. These codes are authentication-wise interlinked and as one single label which can be pre-applied on product-label and still extended authentication challenge like refill-evidence or tamper-evidence in addition to basic counterfeit-evidence.

Abstract: A method and system for performing on-device image to text conversion are provided. Embodiments herein relates to the field of performing image to text conversion and more particularly to performing on-device image to text conversion with an improved accuracy. A method performing on-device image to text conversion is provided. The method includes language detection from an image, understanding of text in an edited image and using a contextual and localized lexicon set for post optical character recognition (OCR) correction.

Abstract: An image processing method, where, in the method, a special image filter is generated, and super-resolution is performed on an image based on the image filter. The image filter includes filter parameters corresponding to each pixel in an image that requires super-resolution processing, and pixels with different texture features correspond to different filter parameters. The image super-resolution method, apparatus, device, and the like may be applied to various scenarios such as a video, a game, and photographing.

Abstract: Technologies are described for retrieving documents using image representations in the documents and is based on intra-image features. The identification of elements within an image representation can allow for deeper understanding of the image representation and for better relating image representations based on their intra-image features. The intra-image features present in image representations can be used in searches. Search results can further be reranked to improve search results. For example, reranking can allow search results to conform to intra-image dominant image features.

Abstract: The present disclosure discloses methods and systems for detecting one or more security patterns in a document submitted at a multi-function device. According to the disclosure the document is received at the multi-function device, wherein the document includes at least textual content. Thereafter, a pre-defined operation is performed to detect edges of the at least textual content. Once detected, one or more text edges are filtered based on one or more templates. Further, based on the one or more templates, shape and color of the filtered one or more text edges are analyzed, and accordingly, the presence of the one or more security patterns is ascertained in the submitted document at the multi-function device.

Abstract: Techniques are described to estimate orientation of one or more cameras located on a vehicle. The orientation estimation technique can include obtaining an image from a camera located on a vehicle while the vehicle is being driven on a road, determining, from a terrain map, a location of a landmark located at a distance from a location of the vehicle on the road, determining, in the image, pixel locations of the landmark, selecting one pixel location from the determined pixel locations; and calculating values that describe an orientation of the camera using at least an intrinsic matrix and a previously known extrinsic matrix of the camera, where the intrinsic matrix is characterized based on at least the one pixel location and the location of the landmark.

Abstract: Disclosed is a method and apparatus for adaptive tracking of a target object. The method includes method of tracking an object, the method including estimating a dynamic characteristic of an object in an input image based on frames of the input image, determining a size of a crop region for a current frame of the input image based on the dynamic characteristic of the object, generating a cropped image by cropping the current frame based on the size of the crop region, and generating a result of tracking the object for the current frame using the cropped image.

Abstract: A method and a device for localization using grid-based localization of map constraints are described. In an example, an indoor space is divided into a grid of tessellated polygonal tiles in a hierarchical structure. The grid is correlated with physical entities in the indoor space by associating each physical entity with a polygonal tile. Further, an absolute probability value indicative of presence of a device therein is associated with each polygonal tile. As part of associating, the absolute probability value is allocated to each polygonal tile in each hierarchical level to create a probability map for the indoor space. The probability map is used to generate a grid map for the indoor space and the grid map is usable to determine location of the device in the indoor space.

Abstract: A method and a system for extracting information from a table in a document is provided. The method includes: receiving a document that includes information that is arranged in a table; determining three sets of coordinates that respectively relate to lines, words, and characters included in the document; extracting a list of lines based on the first set of coordinates; reconstructing the rows of the table based on list of lines and the second set of coordinates; reconstructing the columns of the table based on the reconstructed rows and the third set of coordinates; and outputting a reconstruction of the table. The three sets of coordinates are expressible in an hOCR format that is based on an open standard for representation of scanned information that is obtainable by using an optical character recognition (OCR) technique.

Abstract: An embodiment includes accessing captured video of a first physical object in a physical environment. The embodiment also includes detecting a feature of the first physical object in a first frame of the video. The embodiment encodes a first qubit with a first quantum state based on a first value of the feature of the first physical object, and then entangles the first qubit with a second qubit forming an entangled qubit pair. The embodiment detects a second quantum state of the second qubit of the entangled qubit pair and renders computer-generated content of a virtual environment that includes a computer-generated first virtual object that corresponds to the first physical object, where the rendering comprises determining a property of the first virtual object based on the detected second quantum state.

Abstract: Characteristics of a user's movement are evaluated based on performance of activities by a user within a field of view of a camera. Video data representing performance of a series of movements by the user is acquired by the camera. Pose data is determined based on the video data, the pose data representing positions of the user's body while performing the movements. The pose data is compared to a set of existing videos that correspond to known errors to identify errors performed by the user. The errors may be used to generate scores for various characteristics of the user's movement. Based on the errors, exercises or other activities to improve the movement of the user may be determined and included in an output presented to the user.

Abstract: A method, machine readable medium and system for semantic segmentation of 3D point cloud data includes determining ground data points of the 3D point cloud data, categorizing non-ground data points relative to a ground surface determined from the ground data points to determine legitimate non-ground data points, segmenting the determined legitimate non-ground and ground data points based on a set of common features, applying logical rules to a data structure of the features built on the segmented determined non-ground and ground data points based on their spatial relationships and incorporated within a machine learning system, and constructing a 3D semantics model from the application of the logical rules to the data structure.

Abstract: A distributed systems and methods for generating composite media including receiving a media context that defines media that is to be generated, the media context including: a definition of a sequence of media segment specifications and, an identification of a set of remote devices. For each media segment specification, a reference segment may be generated and transmitted to at least one remote device. A media segment may be received from each of the remote device, the media segment having been recorded by a camera. Verified media sequences may replace the corresponding reference segment. The media segments may be aggregated and an updated sequence of media segments may be defined. An instance of the media context that includes a subset of the updated sequence of media segments may then be generated.

Abstract: An anomaly detection apparatus extracts a circumstantial feature value for anomaly detection corresponding to a circumstantial feature value for learning from other modal signal for anomaly detection different in modal from acoustic, calculates a signal pattern feature related to an acoustic signal of anomaly detection target based on the acoustic signal of anomaly detection target, the circumstantial feature value for anomaly detection and a signal pattern model learned based on an acoustic signal for learning and the circumstantial feature value for learning calculated from other modal signal for learning, and calculates an anomaly score for performing an anomaly detection of the acoustic signal of anomaly detection target based on the signal pattern feature.

Abstract: The disclosure herein describes providing signature data of an input document. Text data of the input document is obtained (e.g., OCR data generated from image data) and a first set of signature fields are identified using signature key-value pairs of the text data. A first subset of signed signature fields and a first subset of unsigned signature fields are determined based on mapping to a set of predicted values. A second set of signature fields are determined using a region prediction model applied to image data of the input document. Region images associated with the first subset of unsigned signature fields and with second set of signature fields are obtained and a second set of signed signature fields and a second set of unsigned signature fields are determined using a signature recognition model. Signature output data is provided including signed signature fields and/or unsigned signature fields.

Abstract: Systems, methods, and devices for estimating a shape of an object based on sensor data and determining a presence of a fault or a failure in a perception system. A method of the disclosure includes receiving sensor data from a range sensor and calculating a current shape reconstruction of an object based on the sensor data. The method includes retrieving from memory a prior shape reconstruction of the object based on prior sensor data. The method includes calculating a quality score for the current shape reconstruction by balancing a function of resulted variances of the current shape reconstruction and a similarity between the current shape reconstruction and the prior shape reconstruction.

Abstract: In order to simplify the control configuration for controlling a driving device and improve reliability of the operation of the driving device, an information processing device includes a detection unit and a processing unit. The detection unit detects the detection target from a captured image by using reference data that is a learning result obtained by machine learning of the detection target including the position of the center of gravity of the object in the captured image. The processing unit controls the driving device to be controlled that acts on the object having the center of gravity detected by the detection unit, by using the detection result of the detection unit.

Abstract: There is provided a sight line position processing apparatus. A detection unit repeatedly detects a sight line position of a user. A first determination unit determines a reliability of the sight line position detected by the detection unit. A generation unit generates a statistical sight line position by calculating a statistical value for a plurality of sight line positions detected by the detection unit. The generation unit controls a number of sight line positions used to calculate one statistical value on the basis of the reliability.

Abstract: The present disclosure includes a video transmission apparatus, a video reception apparatus, an image transmission apparatus, an image reception apparatus, and a system. The image transmission apparatus includes a detection circuitry, a generation circuitry, and a transmission circuitry. The generation circuitry is configured to generate a first image based on a first piece of positional information from a plurality of pieces of positional information, the first image including the overlap region and corresponding to a first region of interest of two or more regions of interest. The generation circuitry is also configured to generate one or more second images based on an overlap region and the plurality of pieces of positional information, the one or more second images excluding the overlap region and corresponding to regions of interest other than the first region of interest of the two or more regions of interest.

Abstract: Embodiments of the present disclosure provide a video processing method and apparatus, a device, a storage medium and a computer program product, where the method includes: playing an audio in a process of capturing a video; playing a first part of the audio at a changing speed according to a first speed change mode in response to recognizing that a target object presents a target state in a captured video image; obtaining a target video according to the captured video image and the audio; and playing, in the target video, a video image captured before the target object presents the target state at a constant speed, and playing, in the target video, a video image captured after the target object presents the target state at a changing speed according to a second speed change mode, where the audio is played at a constant speed.

Abstract: A system and method for processing video data of an object in a movement space comprises uses a plurality of cameras each facing the movement space. An object detection engine running on a processor is in communication with each of the plurality of cameras that transmit video data of the movement space to the processor. The object detection engine determines the coordinates of a bounding box that closely surrounds the object in a frame of the video data from a master camera. The processor then determines, epipolar lines corresponding to points on the bounding box in the frame of the master camera in each of the frames of the video data from the non-master cameras. The processor crops the video data in the frame of the non-master cameras outside two of the epipolar lines to reduce and improve the video data processing.

Abstract: An image processing apparatus having a reading device to read an image from a sheet includes one or more controllers to perform operations. One image is read from one sheet by using the reading device. Edge detection processing is executed on the one image. At least one pair of edges is determined from among a plurality of edges based on information of the plurality of edges detected in the edge detection processing and size information of the one sheet.

Abstract: A method of estimating weight of food objects, includes training an artificial neural network software module, and using the trained artificial neural network software module to provide a weight correlated data estimate for said food object based on a three-dimensional image of the food object.

Abstract: A non-transitory computer-readable storage medium storing a program causes a computer to perform an analysis process based on a radiation moving image in which a dynamic state of a specific site of a subject is captured. The program includes the analysis process in which, an analysis is performed based on the radiation moving image wherein when a plane in which the specific site is movable is to be a movable plane, the radiation moving image is obtained by irradiating radiation on the specific site in a state in which the radiation is orthogonal to the movable plane.

Abstract: Computational systems and methods employ characteristics of a quantum processor determined or sampled between a start and an end of an annealing evolution per an annealing schedule. The annealing evolution can be reinitialized, reversed or continued after determination. The annealing evolution can be interrupted. The annealing evolution can be ramped immediately prior to or as part of determining the characteristics. The annealing evolution can be paused or not paused immediately prior to ramping. A second representation of a problem can be generated based at least in part on the determined characteristics from an annealing evolution performed on a first representation of the problem. The determined characteristics can be autonomously compared to an expected behavior, and alerts optionally provided and/or the annealing evolution optionally terminated based on the comparison. Iterations of annealing evolutions may be performed until an exit condition occurs.

Abstract: Techniques for aligning images generated by two cameras are disclosed. This alignment is performed by computing a relative 3D orientation between the two cameras. A first gravity vector for a first camera and a second gravity vector for a second camera are determined. A first camera image is obtained from the first camera, and a second camera image is obtained from the second camera. A first alignment process is performed to partially align the first camera's orientation with the second camera's orientation. This process is performed by aligning the gravity vectors, thereby resulting in two degrees of freedom of the relative 3D orientation being eliminated. Visual correspondences between the two images are identified. A second alignment process is performed to fully align the orientations. This process is performed by using the identified visual correspondences to identify and eliminate a third degree of freedom of the relative 3D orientation.

Abstract: Methods and apparatus for using selective resolution reduction on images to be transmitted and/or used by a playback device are described. Prior to transmission one or more images of an environment are captured. Based on image content, motion detection and/or user input a resolution reduction operation is selected and performed. The reduced resolution image is communicated to a playback device along with information indicating a UV map corresponding to the selected resolution allocation that should be used by the playback device for rendering the communicated image. By changing the resolution allocation used and which UV map is used by the playback device different resolution allocations can be made with respect to different portions of the environment while allowing the number of pixels in transmitted images to remain constant. The playback device renders the individual images with the UV map corresponding to the resolution allocation used to generate the individual images.

Abstract: Techniques are disclosed for evaluating digital map quality. A process includes steps for receiving change data indicating one or more feature discrepancies associated with one or more geographic regions of a digital map, analyzing the change data to determine which of the one or more feature discrepancies resulted in verified updates to the digital map, and generating a quality score for each of the geographic map regions based on the verified updates. Systems and machine-readable media are also provided.

Abstract: Image transformation tasks such as cropping, text addition etc. are common across industries. Each industry has different business context and demands the image transformations be performed aligned to the business context. This disclosure relates to a system and method for an adaptive image transformation for a given context and maintaining aesthetic sense of the transformed image. Herein, the system is configurable and adaptive to any business context or domain. The system learns the context from available domain samples and creates an automated workflow of context-aware transformation tasks that maintains both the content and aesthetics demands of the context. Further, a saliency map is extracted for the identified RoI to append a text to the RoI based on the extracted saliency map, the calculated similarity metric for various content and aesthetic factors and various preferences of the user.

Abstract: A method of determining a characteristic of one or more processes for manufacturing features on a substrate, the method including: obtaining image data of a plurality of features on a least part of at least one region on a substrate; using the image data to obtain measured data of one or more dimensions of each of at least some of the plurality of features; determining a statistical parameter that is dependent on the variation of the measured data of one or more dimensions of each of at least some of the plurality of features; determining a probability of defective manufacture of features in dependence on a determined number of defective features in the image data; and determining the characteristic of the one or more processes to have the probability of defective manufacture of features and the statistical parameter.

Abstract: An approach provides sending captured Superbill image data and output data generated based on results of parsing the captured Superbill image data to an external system which manages Superbill data via a cloud system and a storage service. The cloud system creates parsing rule data for parsing a captured Superbill image in accordance with user operation at a client device. The cloud system obtains captured Superbill image data from the storage service, in response to receiving a notification indicating that the captured Superbill image data has been stored in the storage service. The cloud system parses the obtained image data based on the created parsing rule and generates output data based on results of parsing. The cloud system sends the generated output data and the obtained image data to the external system via the one or more computer networks.

Abstract: Provided is an electronic device including a first sensor configured to sense a user; a second sensor configured to sense light incident from an external light source; a mirror display; a memory; and a processor configured to: based on the first sensor sensing the user in front of the mirror display, obtain information about a first area in which a first image corresponding to a reflection of the user is located on the mirror display; determine a second area for displaying content to be provided to the user based on the information about the first area; based on information about light being obtained through the second sensor, determine luminance of the second area based on the information about the light; and control the mirror display to display the content with the determined luminance on the second area.

Abstract: An embodiment includes accessing captured video of a first physical object in a physical environment. The embodiment also includes detecting a feature of the first physical object in a first frame of the video. The embodiment encodes a first qubit with a first quantum state based on a first value of the feature of the first physical object, and then entangles the first qubit with a second qubit forming an entangled qubit pair. The embodiment detects a second quantum state of the second qubit of the entangled qubit pair and renders computer-generated content of a virtual environment that includes a computer-generated first virtual object that corresponds to the first physical object, where the rendering comprises determining a property of the first virtual object based on the detected second quantum state.

Abstract: This application discloses a method and apparatus for object detection in an image, a vehicle, and a robot. The method for object detection in an image is performed by a computing device. The method includes determining an image feature of an image; determining a correlation of pixels in the image based on the image feature; updating the image feature of the image based on the correlation to obtain an updated image feature; and determining an object detection result in the image according to the updated image feature.

Abstract: A function execution system includes a function execution device configured to execute a plurality of functions, a storage device, an image acquisition device, and a reader device. The function execution device switches between first to fourth functions to be executed depending on whether code information, which is read by the reader device based on an image representing an information code included in a captured image acquired by the image acquisition device from the image capturing unit, is first code information or second code information and whether user information stored in the storage device is first user information or second user information.

Abstract: Embodiments relate to generating keypoint descriptors of the keypoints using a sub-scale refinement and a sample pattern radius adjustment. An apparatus includes a sub-pixel refiner circuit and a keypoint descriptor generator circuit. The sub-pixel refiner circuit determines a keypoint scale value for a scale dimension of a keypoint in an image pyramid by performing an interpolation of response map (RM) pixel values of a pixel block of RM images defined around the keypoint. The keypoint descriptor generator circuit determines sample scales of the image pyramid based on the keypoint scale value and determines a radius value for each sample scale based on the keypoint scale value. The keypoint descriptor generator circuit samples patches of pixel values at the sample scales using the radius value for each sample scale to generate a keypoint descriptor of the keypoint.

Abstract: A three-dimensional (3D) image-based facial verification method and apparatus is provided. The facial verification method may include capturing a facial image of a 3D face of a user, determining an occluded region in the captured facial image by comparing the captured facial image and an average facial image, generating a synthetic image by synthesizing the captured facial image and the average facial image based on the occluded region, and verifying the user based on the synthetic image.

Abstract: The present disclosure provides an image processing method and apparatus, an electronic device and a storage medium, which relate to the field of computer technology, and more particularly to artificial intelligence technology including computer vision, deep learning and the like. The image processing method includes: recognizing the image to be processed to determine attribute information of each object included in the image to be processed; determining a target thermal image to be recognized according to the attribute information of each object and the image to be processed; reconstructing the target thermal image to generate a first reconstructed image; and determining whether the image to be processed includes an object of a preset class according to a difference between the first reconstructed image and the target thermal image.

Abstract: A method and system for temporal frequency analysis for identification of unmanned aircraft systems. The method includes obtaining a sequence of video image frames and providing a pixel from an output frame of the video; generating a fluctuating pixel value vector; examining the fluctuating pixel value vector over a period of time; obtaining the frequency information present in the pixel fluctuations; summing the frequency coefficients for the vectorized pixel values from the fluctuating pixel value vector; obtaining an image representing a two dimensional space based on the summed center frequency coefficients; generating a series of still frames equal to a summation of the center frequency coefficients for pixel variations; and combining the temporal information into spatial locations in a matrix to provide a single image containing the spatial and temporal information present in the sequence of video image frame.

Abstract: An image segmentation method according to an embodiment of the present invention is performed in a computing device having one or more processors and memory for storing one or more programs executed by means of the one or more processors, and includes the steps of: (a) receiving the input of an image; (b) generating a first-generation image segment set by dividing the input image in an overlapped manner; and (c) generating a second or higher-generation image segment set from the first-generation image segment set, wherein a subsequent-generation image segment set is generated by dividing in an overlapped manner at least one of a plurality of image segments included in the previous-generation image segment set.

Abstract: The present disclosure provides a method and an apparatus for determining an attitude angle of a camera, capable of improving the accuracy of the attitude angle of the camera, and in turn the accuracy of the attitude of the camera that is obtained based on the attitude angle of the camera. The present disclosure can also improve the accuracy of object distance measurement and vehicle positioning based on the attitude angle of the camera. In the method for determining an attitude angle of a camera, the camera is fixed to one and the same rigid object in a vehicle along with an Inertial Measurement Unit (IMU).

Abstract: The subject technology receives assessment values determined by a first machine learning model deployed on a client electronic device, the assessment values being indicative of classifications of input data and the assessment values being associated with constraint data that comprises a probability distribution of the assessment values with respect to the classifications of the input data. The subject technology applies the assessment values determined by the first machine learning model to a second machine learning model to determine the classifications of the input data. The subject technology determines whether accuracies of the classifications determined by the second machine learning model conform with the probability distribution for corresponding assessment values determined by the first machine learning model.

Abstract: Method and apparatus for overlaying themed imagery onto real-world objects in a head-mounted display device (HMDD). A computing device receives, from an HMDD, depth data that identifies distances from the HMDD to surfaces of a plurality of objects in a user space. The computing device detects at least one object in the user space based at least in part on the depth data. The computing device determines a classification of video content being presented on a display system of the HMDD. The computing device selects, based on the classification, a particular image theme from a plurality of different image themes, the image theme comprising one or more image textures. The computing device sends, to the HMDD, at least one image texture for overlaying the at least one object during presentation of the at least one object on the display system of the HMDD in conjunction with the video content.