Abstract: Techniques for interactively determining/visualizing the color content of a source image and how the corresponding image data is mapped to device colors are described herein. For example, the color content of a digital image can be converted between different color spaces to identify gamut limitations of an output device (e.g., a printing assembly), discover color(s) that cannot be accurately reproduced, etc. Color space conversions enable the transformation of the color content of the digital image from device-specific colorants to a device-independent representation (and vice versa). In some embodiments, these transformations are facilitated using lookup tables that are implemented in graphical processing unit-resident memory.

Abstract: Techniques for interactively determining/visualizing the color content of a source image and how the corresponding image data is mapped to device colors are described herein. For example, the color content of a digital image can be converted between different color spaces to identify gamut limitations of an output device (e.g., a printing assembly), discover color(s) that cannot be accurately reproduced, etc. Color space conversions enable the transformation of the color content of the digital image from device-specific colorants to a device-independent representation (and vice versa). In some embodiments, these transformations are facilitated using lookup tables that are implemented in graphical processing unit-resident memory.

Abstract: An electronic chip and a chip assembly are described. The electronic chip comprises one or more processing cores and at least one hardware interface coupled to at least one of the one or more processing cores. At least one of the one or more processing cores implements a game engine in hardware.

Abstract: Disclosed are face clustering method and apparatus, image classification storage method, computer-readable storage medium and electronic device.

Abstract: An apparatus, and method of operating the same locates and tracks a target in four dimensions across a FPA using GMAPD data. The apparatus includes a receiver and a processor arranged to generate a video filter array, the video filter array including a set of estimated velocity pixel coordinate components arranged in a linear data set. The processor generates detected photo events based on received scattered laser pulses, filters the detected photo events by linearly indexing each of the plurality of detected photo events based on, for each detected photo event, a vertical position in the focal plane array, a horizontal position in the focal plane array, a frame number, and the dimensions of the focal-plane array. The processor maps each detected photo event to the set of estimated velocity pixel coordinate components, and generates a motion-compensated image associated with the mapped detected photo events in a filtered two-dimensional array.

Abstract: The present application discloses a chromaticity adjustment method and an adjustment device of a display panel. The chromaticity adjustment method of the display panel includes: determining an initial driving voltage corresponding to a highest gray scale of the display panel; acquiring an initial white picture chromaticity of the display panel based on the initial driving voltage; determining whether the initial white picture chromaticity deviates from a target white picture chromaticity; if the initial white picture chromaticity deviates from the target white picture chromaticity, adjusting the initial driving voltage to adjust the initial white picture chromaticity.

Abstract: Dense feature scale detection can be implemented using multiple convolutional neural networks trained on scale data to more accurately and efficiently match pixels between images. An input image can be used to generate multiple scaled images. The multiple scaled images are input into a feature net, which outputs feature data for the multiple scaled images. An attention net is used to generate an attention map from the input image. The attention map assigns emphasis as a soft distribution to different scales based on texture analysis. The feature data and the attention data can be combined through a multiplication process and then summed to generate dense features for comparison.

Abstract: A multi-source image correspondence method and system based on heterogeneous model fitting is provided, the method includes the following steps: constructing a multi-orientation phase consistency model, fusing phase consistency, image amplitude, and orientation detection feature points, constructing logarithmic polar coordinate descriptors with variable-size bins using sub-region grids and orientation histograms, effectively estimating model parameters through heterogeneous model fitting, accumulating matching pairs from different heterogeneous models that meet a preset joint position offset transformation error, outputting a final matching pair, and completing multi-source image correspondence.

Abstract: Apparatus, systems, and method for user presence detection for audience monitoring are disclosed. Example apparatus disclosed herein are to detect movement of a user relative to an area based on one or more signals output by one or more motion detection sensors, the area associated with a media presentation device. Disclosed example apparatus are also to generate a request for verification of user presence in the viewing area in response to detection of the user movement. Disclosed example apparatus are further to correlate a user input responsive to the request with media presented via the media presentation device.

Abstract: A learning device is configured to perform learning by gradient boosting, and includes: data memory units configured to store learning data including a type of feature amount and corresponding gradient information; gradient output units each configured to receive an input of the feature amount and the corresponding gradient information from a corresponding one of the data memory units, and output the gradient information through an output port corresponding to each value of the input feature amount; an addition unit configured to add up one or more pieces of the gradient information corresponding to the same value of the feature amount, and output an added value of the gradient information corresponding to each value of the feature amount; and a histogram memory unit configured to store a histogram obtained by integrating added values of the gradient information corresponding to each value of the feature amount as a bin.

Abstract: Provided is a method of detecting a semantics section in a video. The method includes extracting all video features by inputting an inputted video to a pre-trained first deep neural network algorithm, extracting a query sentence feature by inputting an inputted query sentence to a pre-trained second deep neural network algorithm, generating video-query relation integration feature information in which all of the video features and the query sentence feature have been integrated by inputting all of the video features and the query sentence feature to a plurality of scaled-dot product attention layers, and estimating a video segment corresponding to the query sentence in the video based on the video-query relation integration feature information.

Abstract: A system for monitoring shopping carts uses cameras to generate images of the carts moving in a store. In some implementations, cameras may additionally or alternatively be mounted to the shopping carts and configured to image cart contents. The system may use the collected image data, and/or other types of sensor data (such as the store location at which an item was added to the basket), to classify items detected in the shopping carts. For example, a trained machine learning model may classify item in a cart as “non-merchandise,” “high theft risk merchandise,” “electronics merchandise,” etc. When a shopping cart approaches a store exit without any indication of an associated payment transaction, the system may use the associated item classification data, optionally in combination with other data such as cart path data, to determine whether to execute an anti-theft action, such as locking a cart wheel or activating a store alarm.

Abstract: A system, non-transitory computer readable medium and method for detecting anomalous activity based on a data distribution is disclosed. The system includes a processor, and a memory coupled to the processor. The memory stores computer executable instructions that, when executed by the processor, cause the processor to obtain a plurality of datapoints defining a data distribution. The processor classifies the plurality of datapoints as isolated or non-isolated datapoints, and clusters at least some of the non-isolated datapoints into at least one mode segment. A reference mode from the at least one mode segment is identified, and at least one outlier being either an isolated or non-isolated datapoint separated from the reference mode by a predetermined number of isolated datapoints representing a flat portion is identified. An action is initiated based on the identified at least one outlier.

Abstract: This image change detection device includes a subspace updating unit that, when a determination unit determines that there has been no change, updates a first subspace by rotating the first subspace so that the first subspace approaches a second subspace. When the determination unit determines that there has been no change, a degree-of-change calculating unit calculates the degree of change between the first subspace updated by the subspace updating unit and a second subspace whose bases are left singular vectors of an image in a change detection period next to a change detection period.

Abstract: In an example, a method includes, by one or more processors, receiving a greyscale image having a plurality of pixels, each pixel being associated with a grey level, and the greyscale image having a first number of grey levels. An order of the pixels may be determined based on the grey level. A second number of grey levels may be determined, wherein the second number of grey levels is greater than the first number, and an indication of a target number of pixels per grey level of the second number of grey levels may be further be determined. Taking the pixels in order, and based on the target number of pixels per grey level, a new grey level may be allocated to each pixel to provide the second number of grey levels. The new grey levels may be converted to a threshold of a threshold halftone screen.

Abstract: Systems, methods, and computer program products for thermal contrast determinations are provided. An example imaging system includes a first infrared (IR) imaging device that generates first IR image data of a field of view of the first IR imaging device and a computing device connected with the first IR imaging device. The computing device receives probe temperature data from a temperature probe indicative of an external environment of the imaging system and receives the first IR image data from the first IR imaging device. The computing device determines background temperature data based upon the first IR image data, determines gas temperature data based upon the probe temperature data, and determines a thermal contrast for each pixel based upon a comparison between the background temperature data and the gas temperature data. The computing device further determines a detection limit for each pixel as a function of thermal contrast.

Abstract: Various embodiments provide an electronic device including: a camera comprising an image signal processor configured to process a video output from an image sensor; a memory; and a processor, wherein the processor is configured to: obtain the processed video from the image signal processor; extract a portion of the obtained video to detect motion; synchronize the obtained video with the extracted video, based on the motion detection; produce a slow motion video by converting a frame rate of the synchronized video; and encode the produced slow motion video and store the same in the memory, and a method thereof. Various embodiments may be provided.

Abstract: An electronic apparatus for performing machine learning a method of machine learning, and a non-transitory computer-readable recording medium are provided. The electronic apparatus includes an operation module configured to include a plurality of processing elements arranged in a predetermined pattern and share data between the plurality of processing elements which are adjacent to each other to perform an operation; and a processor configured to control the operation module to perform a convolution operation by applying a filter to input data, wherein the processor controls the operation module to perform the convolution operation by inputting each of a plurality of elements configuring a two-dimensional filter to the plurality of processing elements in a predetermined order and sequentially applying the plurality of elements to the input data.

Abstract: Adaptive acquisition control includes obtaining a processed image by an image capture apparatus, which includes, a target exposure component that obtains a target exposure value in accordance with target exposure input data, an aggregate gain component that obtains a target aggregate gain value and a remaining gain value in accordance with aggregate gain input data, an auto-exposure compensation component that obtains an auto-exposure compensation tone curve in accordance with auto-exposure compensation input data, a contrast control component that obtains a contrast control tone curve and a contrast control black point value, and a tone control driver that obtains a tone control tone curve and a tone control black point value, and an image signal processor that processes the current input image in accordance with the tone control tone curve and the tone control black point value to produce the processed image.

Abstract: One variation of a method includes, at a sensor block: detecting a set of objects within a region-of-interest in a frame; detecting an object type of each object; detecting a location of each object within the region-of-interest; and storing object types and object locations of the set of objects in a set of containers. The method further includes, at the computer system: accessing a database of commissioning images; extracting a commissioning image annotated with boundaries from the database; initializing a visualization layer of a set of pixels representing the region-of-interest; and calculating a frequency of presence of the object type intersecting each pixel based on the set of containers; calculating a color value for each pixel based on the frequency of presence; and assigning the color value to each pixel in the visualization layer; and generating a heatmap of the region-of-interest based on the visualization layer and the commissioning image.

Abstract: A system for detecting a scan irregularity in scanning process during check-out at a retail store, includes an image receiving module for receiving a video stream of a scanning zone, an image processing module for detecting visual scan intervals in image frames of the video stream, and a decision module. The decision module is configured to process each detected visual scan interval, wherein a processed visual scan interval includes a valid scan action, wherein the valid scan action is a user action performed for scanning an item. The decision module is further configured to detect a scan irregularity in the check-out process, wherein the scan irregularity occurs when an item identified for scanning in a processed visual scan interval is absent in a list of scanned items generated by the scanner during corresponding interval, and provide an alert regarding the scan irregularity at a user computing device.

Abstract: Disclosed is a localization method and apparatus that may acquire localization information of a device, generate a first image that includes a directional characteristic corresponding to an object included in an input image, generate a second image in which the object is projected based on the localization information, to map data corresponding to a location of the object, and adjust the localization information based on visual alignment between the first image and the second image.

Abstract: There is provided a computer implemented method comprising: displaying, via a display of an augmented reality, AR, device, a view of image data obtained by a camera of the AR device; tracking a position of a target object within the displayed view; determining a visibility of the tracked target object and/or a virtual object to be superimposed on the tracked target object on the display, wherein the position of the virtual object is dependent on the position of the target object; and generating a trigger signal depending on the visibility.

Abstract: Disclosed is a system and associated methods that account for the change in coloring or tint that some wavelengths of light have on materials of an object, and that generate an object model with the accounted for change in coloring or tint removed from the pixels or constructs of that model. The system receives spectral data in different electromagnetic spectrum bands for a particular surface of the object. The system measures a first quality of the light that illuminates the object, and determines a reactivity of the particular surface to the first quality of the light based on the spectral data matching a spectral signature of a material having that reactivity. The system removes the light effects on the particular surface by adjusting the spectral data according to the reactivity to the first quality of the light and measuring the first quality in the light illuminating the object.

Abstract: A generic gesture detecting method executed by a generic gesture detecting device includes steps of: receiving a current sensing signal from a sensing unit; generating a current image according to the current sensing signal; determining whether the current image is similar with a stored image stored in a memory unit; when the current image is similar with the stored image, detecting the current image and the stored image to be a gesture signal; when the current image is different from the stored image, storing the current image into the memory unit, and returning to the step of receiving a current sensing signal. Since the generic gesture detecting device can automatically detect the gesture signal, the user may not need to enable a detecting time period before implementing a command motion. Therefore, the user can make the command motion without enabling the detecting time period, and the convenience can be increased.

Abstract: Aspects of the present disclosure provide techniques for document classification through signal processing. Embodiments include receiving a document for classification. Embodiments include generating an image of the document. Embodiments include producing a signal representation of the document based on numbers of non-white pixels in each horizontal scan line or vertical scan line of the image of the document. Embodiments include comparing the signal representation of the document to signal representations of previously-classified documents. Embodiments include determining, based on the comparing, a classification for the document. Embodiments include performing additional processing with respect to the document based on the classification for the document.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed. An example apparatus includes an audio detector to determine a first audience count based on signatures of audio data captured in the media environment, a thermal image detector to determine a heat blob count based on a frame of thermal image data captured in the media environment, and an audience image detector to identify at least one audience member based on a comparison of a frame of audience image data with a library of reference audience images, the audience image detector to perform the comparison in response to the first audience count not matching the heat blob count.

Abstract: Apparatus, systems, and method for user presence detection for audience monitoring are disclosed. Example apparatus disclosed herein are to detect movement of a user relative to an area based on one or more signals output by one or more motion detection sensors, the area associated with a media presentation device. Disclosed example apparatus are also to generate a request for verification of user presence in the viewing area in response to detection of the user movement. Disclosed example apparatus are further to correlate a user input responsive to the request with media presented via the media presentation device.

Abstract: Disclosed are a system and methods for operating an autonomous or semi-autonomous vehicle. One method comprises travelling in an outdoor setting, capturing data related to the outdoor setting, processing captured data and identifying occlusion present in the preprocessed data. The system comprises an autonomous or semi-autonomous vehicle configured to travel in outdoor settings and comprising at least one first sensor and at least one processing component. The processing component is configured to process data captured by the first sensor and identify occlusion present in the preprocessed data.

Abstract: A system and method for identifying damage to an embankment includes acquiring satellite imagery of an area of the embankment, generating a set of input data from the satellite imagery, removing at least one anomaly in the set of input data to obtain a cleaned set of input data, and identifying the damage by determining a dam motion area indicative of ground motion in the embankment from the cleaned set of input data and determining an anomalous vegetation area and an anomalous wetness area indicative of seepage in the embankment from the cleaned set of input data.

Abstract: A method for local automatic white balance (AWB) of wide dynamic range (WDR) images is provided that includes collecting statistics for local AWB by an image signal processor (ISP) from a first WDR image generated by the ISP, receiving, by the ISP, a plurality of local gain lookup tables (LUTs), one for each color channel, wherein the plurality of local gain LUTs is generated using the statistics, and applying, by the ISP, a gain value to each pixel in a second WDR image generated by the ISP, wherein the gain value for the pixel is determined by the ISP using the local gain LUT for the color channel of the pixel.

Abstract: Systems and methods for detecting anatomical structures include, for each training subject of a plurality of training subjects, a corresponding MR image, and generating an initial anatomical template based on a first training subject of the plurality of training subjects. A computing device can map MR images of the other training subjects onto a template space by applying a global transformation followed by a local transformation. The computing device can average the mapped MR images with the initial anatomical template to generate a final anatomical template and boundaries of an anatomical structure of interest can be drawn in the final anatomical template. The computing device can fine tune the boundaries using an edge detection algorithm. The final anatomical template can be used to identify boundaries of the anatomical structure(s) of interest automatically (e g., without human intervention) in non-training subjects.

Abstract: A system and method are provided for optimizing histogram cumulative distribution function curves. In use, a first cumulative distribution function for a first histogram of a first pixel region of a first image is computed, and a first set of parameters for the first cumulative distribution function is extracted. A second cumulative distribution function for a second histogram of a second pixel region of the first image is computed, and a second set of parameters for the second cumulative distribution function is extracted. An interpolated cumulative distribution function comprising interpolated parameters calculated by interpolating between the first set of parameters and the second set of parameters is created. Additionally, a first equalized pixel in a second image based on a first input pixel in the first image and the interpolated cumulative distribution function is generated.

Abstract: An image processing device and an image processing method are provided. The image processing device comprises a receiving module, a interface conversion module, a selecting module, and a controller. The receiving module is configured to receive image signals. The interface conversion module is configured to convert the image signals into converted image signals with a target image interface. The selecting module is configured to generate at least two selected image signals from the converted image signals according to the first selecting signal. The controller is configured to provide the first selecting signal to selecting module. The image processing device generates the composite image by overlaying the at least two selected image signals.

Abstract: In a method for embedding user information in webpages, user information of a user who logs into a target website is obtained. The user information is converted into color values. The color values are embedded in a target webpage of the target website. If a webpage is leaked, a user who leaks the webpage can be traced.

Abstract: A system and method for tracing polygons in a drawing source file. The method includes extracting vector imagery from the source file, creating a planar representation of the vector imagery as a plurality of lines, filtering the plurality of lines to create simplified line art, morphologically dilating the simplified line art to generate a polygonal approximation, calculating geometric difference between the source file canvas bounds and the polygonal approximation to identify contracted polygons, morphologically dilating the contracted polygons to create visual polygons, and filtering the visual polygons according to one or more geometric parameters to identify salient polygons.

Abstract: A method is provided for identifying improperly redacted information in documents. The documents are analyzed to detect redacted areas and text elements and to identify an intersection between a redacted area and a text element. When an area of the intersection is greater than an intersection threshold, the document is identified as containing improperly redacted information.

Abstract: Certain embodiments involve flow-based color transfers from a source graphic to target graphic. For instance, a palette flow is computed that maps colors of a target color palette to colors of the source color palette (e.g., by minimizing an earth-mover distance with respect to the source and target color palettes). In some embodiments, such color palettes are extracted from vector graphics using path and shape data. To modify the target graphic, the target color from the target graphic is mapped, via the palette flow, to a modified target color using color information of the source color palette. A modification to the target graphic is performed (e.g., responsive to a preview function or recoloring command) by recoloring an object in the target color with the modified target color.

Abstract: In accordance with various aspects of the present disclosure, methods and systems for fire detection are disclosed. In some embodiments, a method for fire detection includes: acquiring data related to a monitored area, wherein the data comprises image data related to the monitored area; determining, based on the acquired data, whether a first mode or a second mode is to be executed for fire detection, wherein the first mode comprises a first smoke detection, and the second mode comprises a first flame detection; and executing, by a hardware processor, at least one of the first mode or the second mode based on a result of the determination.

Abstract: An image processing apparatus including a determination unit configured to determine, for each of a plurality of partial areas set in an input image, a priority for executing a first image analysis process, based on an image of the partial area and a corresponding image corresponding to the partial area, the corresponding image being in a past image analyzed before the input image, a selection unit configured to select at least one of partial areas from the plurality of partial areas, based on the determined priority, and a first analysis unit configured to execute the first image analysis process on each of the at least one of partial areas selected.

Abstract: Techniques for machine-based identification of objects extracted from text documents in natural language are disclosed. An example method may comprise: identifying matching pairs of one or more information objects corresponding to a real world object, one information object from the document and at least one information object from the document storage for a combination of global identification patterns that exist in the document and in the document storage; ascertaining consistency of the matching pairs and determining which of the one or more information objects in the document are suitable for merging into the document storage; and adding the one or more information objects from the document to the document storage to associate information objects corresponding to the real world object.

Abstract: Techniques for performing a prediction task using a multi-modal statistical model configured to receive input data from multiple modalities including input data from a first modality and input data from a second modality different from the first modality.

Abstract: A server system includes a database for storing data, a memory device for storing data selected from the data in the database, and a processing device that selects data from the database, stores the selected data in the memory device, and transmits over a communication network an availability signal to a client, the availability signal including an identifier of the selected data and indicating that the selected data is stored in the memory device and is available to be accessed by the client.

Abstract: Techniques for multistage process model training are described herein. Another aspect includes determining a first gray level histogram corresponding to a first input image. Another aspect includes determining a second gray level histogram corresponding to a second input image. Another aspect includes determining a set of change values, each change value corresponding to a change in a respective gray level from the first gray level histogram to the second gray level histogram. Another aspect includes comparing each change value of the set of change values to a threshold. Another aspect includes, based on determining that a first change value of the set of change values is higher than the threshold, adding a first gray level corresponding to the first change value to a hot zone of the second input image. Another aspect includes training a model using the hot zone of the second input image.

Abstract: Embodiments allow a viewer of a display to see images. The images viewed by the glasses may be based on the orientation of the glasses, so that the images correspond to the user's viewpoint. Different images may be presented to left and right eyes for 3D stereoscopic viewing. The position and orientation of the glasses may be tracked by analyzing images from one or more cameras observing the glasses. Glasses may have distinct geometric shapes or features, such as circular lenses, rims, regions around the lenses, to facilitate tracking. One or more regions of the glasses may be illuminated by self-contained or reflected light, to facilitate tracking under various ambient lighting conditions. The lenses of the glasses may have selective barriers such as anaglyph filters, polarizing filters, and shutters, to select images from the display.

Abstract: Provided are an artificial intelligence (AI) system using a machine learning algorithm like deep learning, or the like, and an application thereof. A robotic cleaning apparatus that generates map data includes a communication interface comprising communication circuitry, a memory configured to store one or more instructions, and a processor configured to control the robotic cleaning apparatus by executing the one or more instructions. The processor is configured, by executing the one or more instructions, to control the robotic cleaning apparatus to: generate basic map data related to a cleaning space, and generate object information regarding at least one object in the cleaning space, the object information being generated based on information obtained by the robotic cleaning apparatus regarding the object in a plurality of different positions of the cleaning space, and including information about a type and a position of the object.

Abstract: A computer-implemented method for assessing material microstructure of a machine component involves obtaining a raw image of a section of the component captured via a microscope. The method further includes pre-processing the raw image to generate a ternary image defined by pixel data including three levels of intensities. The method further includes identifying, from the ternary image, phase boundaries delineating at a phase in a primary constituent material of the component. The method further includes determining a volume associated with the phase based on the identified phase boundaries. The proposed method may be utilized, for example, as an automated tool for assessing material degradation and for quality control of gas turbine engine components.

Abstract: The present disclosure provides an image processing method, an image processing device and an electronic device. The image processing method is configured to process scene data acquired by an imaging device. The scene data includes a first scene image. The method includes: processing the scene data to obtain a scheme of the first scene image; and processing the first scene image corresponding to the scheme, to enhance contrast between the scheme of the first scene image and a remaining part of the first scene image.

Abstract: In a feature extraction apparatus, a small region setter divides an object region set in a captured image into small regions smaller in size than the object region. A small region extractor extracts, from each small region, a small-region feature that has two or more feature parameters associated with the corresponding small region. A feature calculator calculates a product of a first feature representing the small-region feature of a first small region selected as a target region from the small regions, and a second feature representing the small-region feature of a second small region in the small regions, the second small region having a predetermined positional relationship with the first small region. The feature calculator obtains, based on the product of the first feature and the second feature, an image feature for the first small region as the target region.

Abstract: Embodiments of the invention are directed to using image data and contextual data to determine information about a scene, based on one or more previously obtained images. Contextual data, such location of image capture, can be used to determine previously obtained images related to the contextual data and other location-related information, such as billboard locations. With even low resolution devices, such as cell phone, image attributes, such as a histogram or optically recognized characters, can be compared between the previously obtained images and the newly captured image. Attributes matching within a predefined threshold indicated matching images. Information on the content of matching previously obtained images can be provided back to a user who captured the new image. User profile data can refine the content information. The content information can also be used as search terms for additional searching or other processing.