Abstract: Systems and methods for image processing are described. Embodiments of the present disclosure receive an image having a plurality of object instances; encode the image to obtain image features; decode the image features to obtain object features; generate object detection information based on the object features using an object detection branch, wherein the object detection branch is trained based on a first training set using a detection loss; generate semantic segmentation information based on the object features using a semantic segmentation branch, wherein the semantic segmentation branch is trained based on a second training set different from the first training set using a semantic segmentation loss; and combine the object detection information and the semantic segmentation information to obtain panoptic segmentation information that indicates which pixels of the image correspond to each of the plurality of object instances.

Abstract: A construct information management system and method for enabling handling of different types of data is provided. A construct information management system 1 for managing information related to a construct includes: a data collection unit 11 configured to collect different types of source data related to different types of constructs from prescribed data sources 2A, 2B, 3A, 3B and retain the collected source data; and a data management unit 12 configured to map the collected source data onto a prescribed spatiotemporal model, acquire prescribed data associated with input data on the basis of at least mapping information on the prescribed spatiotemporal model, and process and output the acquired prescribed data.

Abstract: A method of identifying data items by wave blocks, each wave block comprising a set of unique features distinguishable from the unique features of other wave blocks. The unique features of the wave blocks are extracted and stored. A plurality of wave tags are defined, each comprising a set wave blocks. A mapping of the set of wave blocks to each wave tag is stored. A request for a wave tag to identify a data item is received and a wave tag is assigned to the data item. The wave tag is broadcasted and is captured by a capturing device, which extracts the unique features of the wave blocks. The wave tag is identified by comparing the extracted features of the wave blocks with the stored features of the plurality of wave blocks. The data item is identified from the mapping of the data item to the wave tag.

Abstract: An automatic seismic facies identification method based on combination of Self-Attention mechanism and U-shape network architecture, including: obtaining and preprocessing post-stack seismic data to construct a sample training and validation dataset; building an encoder through an overlapped patch merging module with down-sampling function and a self-attention transformer module with global modeling function; building a decoder through a patch expanding module with linear upsampling function, the self-attention transformer module, and a skip connection module with multilayer feature fusion function; building a seismic facies identification model using the encoder, the decoder, and a Hypercolumn module, where the seismic facies identification model includes a Hypercolumns-U-Segformer (HUSeg); and building a hybrid loss function; iteratively training the seismic facies identification model with a training and validation set; and inputting test data into a trained identification model to obtain seismic facies co

Abstract: Systems and methods for providing encryption and decryption involving texture warping, comprising: obtaining a visual input; obtaining a private key; generating an encrypted visual representation (visual representation A) based on the private key and the visual input; determining at least one 3D object configured so that the private key is derivable when the visual representation A is mapped to a digital model of the at least one 3D object; transmitting the visual representation A to a second computing device associated with a second user; transmitting a representation of the digital model of the at least one 3D model to the second computing device; and instructing the second computing device so that the second computing device is configured to map the visual representation A to the digital model generated based on the representation of the digital model of the at least one 3D model to extract the private key.

Abstract: There is provided an inspection device, an inkjet printing apparatus, and an inspection method capable of accurately inspecting a printed image printed on a surface of a transparent base material. A first light-emitting unit (61) emits light from one side of a transparent base material (9) toward the transparent base material (9). An imaging unit (63) images the transparent base material (9) from the other side of the transparent base material (9). As described, the first light-emitting unit (61) and the imaging unit (63) are disposed on the opposite sides of the transparent base material (9). As a result, it is possible to suppress generation of the shadow of a printed image itself in a captured image (D1). Therefore, the printed image can be accurately inspected based on the captured image (D1) obtained.

Abstract: Various implementations disclosed herein include devices, systems, and methods that provide color visual markers that include colored markings that encode data, where the colors of the colored markings are determined by scanning (e.g., detecting the visual marker using a sensor of an electronic device) the visual marker itself. In some implementations, a visual marker is detected in an image of a physical environment. In some implementations, the visual marker is detected in the image by detecting a predefined shape of a first portion of the visual marker in the image. Then, a color-interpretation scheme is determined for interpreting colored markings of the visual marker that encode data by identifying a set of colors at a corresponding set of predetermined locations on the visual marker. Then, the data of the visual marker is decoded using the colored markings and the set of colors of the color-interpretation scheme.

Abstract: Embodiments described herein relate to a method for probabilistically forecasting the state of hardware components. The method may include obtaining data items corresponding to a hardware component and performing an analysis of the hardware component. The analysis may include making a variety of probability predictions as to whether a label from among a set of possible labels is likely to be the correct label. The set of probabilities from the aforementioned analysis are then analyzed to determine which predicted label has the tightest range, and the prediction with the tightest range for a certain label is displayed to a user in a ranked fashion that includes a quantity of such probability prediction ranges. Such a display may allow an administrator to take action as to which hardware components should be replaced and in what order.

Abstract: Concepts and technologies directed to surrogate metadata aggregation for dynamic content assembly are disclosed. Embodiments can include a system that comprises a processor and a memory that stores computer-executable instructions that configure a processor to perform operations. The operations can include obtaining a first visual content from a digital data store, where the first visual content is configured to digitally represent a first scene. The operations can include performing image recognition on the first visual content so as to identify a second visual content that is digitally configured to represent a second scene. The operations can include determining that native original metadata cannot be obtained for the first visual content, where the native original metadata includes information about the first scene digitally represented by the first visual content.

Abstract: An image transformation method includes: obtaining identification information of an original image; converting the identification information to an identification image; performing frequency domain transformation on the original image to obtain a pixel matrix of the original image in a frequency domain space; performing matrix decomposition on the pixel matrix to obtain an image brightness matrix; converting pixel values of corresponding pixels in the image brightness matrix based on pixel values of pixels in the identification image to obtain a converted brightness matrix; and performing inverse frequency domain transformation on the converted brightness matrix to obtain a transformed image including invisible identification information, and adding the invisible identification information to the original image.

Abstract: Described are techniques for generating, updating, and using sensor-based navigational maps. An input map is generated based on sensor data captured by a first sensor of a first vehicle. The input map is filtered based on one or more criteria to generate a filtered map corresponding to a three-dimensional representation of a route traveled by the first vehicle. The filtering can be based on detecting features using sensor data captured by a second sensor of the first vehicle. The one or more criteria can include object classes, distance criteria, and/or other criteria relating to attributes of features in the sensor data captured by the first sensor and/or the sensor data captured by the second sensor. The filtered map can be stored for transmission to a second vehicle, for use in determining a location of the second vehicle while the second vehicle is traveling along the same route.

Abstract: In some embodiments, a method receives a first sequence of inputs for processing via a sub-model of a plurality of sub-model. The plurality of sub-models are part of a main model. An input in the sequence of inputs is masked with a masked value to generate a second sequence of inputs. The method processes the second sequence of inputs using the sub-model to generate a sequence of features that correspond to the second sequence of inputs and processes the sequence of features to generate a first output. The first output is processed to generate a second output of the main model. The sub-model is trained based on a feature in the sequence of features that corresponds to the masked input and the second output.

Abstract: Using various embodiments, methods and systems for verification of a digital asset owner in a digital environment are described. In one embodiment, a system is configured to receive a non-fungible token (NFT) associated with a digital asset, the NFT providing proof of ownership of the digital asset through a cryptographic public key and retrieve the digital asset. The system then retrieves a secret pattern from the digital asset, wherein the secret pattern was previously embedded into the digital asset, the secret pattern associated with the cryptographic public key and computes a first identification hash value using a hash function, the hash function receiving a parameter value derived from the secret pattern. The system then receives a second identification hash value and compares the first identification hash value to the second identification hash value. If the first and second identification hash values are identical, then the digital asset is determined to be authentic.

Abstract: An image processing device receives a caption for an image before, during, or after capture of the image by an image capture device. The image processing device generates image processing settings based on the caption, for instance based on a mood indicated in the caption or an object identified in the caption. If the caption is received before image capture, the image processing settings may include image capture settings that the image capture device may use to alter exposure or focus during image capture. Once the image is captured, the image processing device may process the image based on the image processing settings, for instance by applying filters or adjusting gain, brightness, contrast, saturation, or colors. For instance, brightness and saturation may be altered if the caption indicates a happy or sad mood, and focus may be altered to focus on an object identified in a caption.

Abstract: Systems and methods are disclosed for analyzing an image of a slide corresponding to a specimen, the method including receiving at least one digitized image of a pathology specimen; determining, using the digitized image at an artificial intelligence (AI) system, at least one salient feature, the at least one salient comprising a biomarker, cancer, cancer grade, parasite, toxicity, inflammation, and/or cancer sub-type; determining, at the AI system, a salient region overlay for the digitized image, wherein the AI system indicates a value for each pixel; and suppressing, based on the value for each pixel, one or more non-salient regions of the digitized image.

Abstract: Computer implemented methods and computerized apparatus are provided for global registration between a first point cloud and a second point cloud obtained by a scanning device on an identical spatial scene at two separate instances. The method comprises extracting a first set of discriminative line-pairs from the first point cloud and a second set of discriminative line-pairs from the second point cloud, wherein a discriminative line-pair is a line-pair having high discriminative power compared to a randomly selected line-pair. In some embodiments, then a plurality of matching line-pair groups between the two sets of discriminative line-pairs are identified in accordance with one thresholding criterion related to between-line relationship, line geometry and line location; and a compass angle criterion related to compass errors of the scanning device. The method further comprises finding most reliable correspondence between the two point clouds by voting and then computing a global transformation matrix.

Abstract: An information processing apparatus (2000) detects one or more candidate regions (22) from a captured image (20) based on an image feature of a target object. Each candidate region (22) is an image region that is estimated to represent the target object. The information processing apparatus (2000) detects a person region (26) from the captured image (20) and detects an estimation position (24) based on the detected person region (26). The person region (26) is a region that is estimated to represent a person. The estimation position (24) is a position in the captured image (20) where the target object is estimated to be present. Then, the information processing apparatus (2000) determines an object region (30), which is an image region representing the target object, based on each candidate region (22) and the estimation position (24).

Abstract: A spatial monitoring system employs a partial dimension iterative closest point analysis to provide improved accuracy for point cloud registration. The partial dimension iterative closest point analysis improves registration accuracy by performing optimization in accordance with an error magnitude of each dimension, wherein dimensions having large initial errors are significantly improved, and dimensions having high initial accuracy are further improved. The registration separately optimizes each dimension using surfaces with contributing information for the optimized dimension.

Abstract: The present invention discloses a method for point cloud up-sampling based on deep learning, including: obtaining training data including a first number of sparse input points and a second number of dense input points; constructing a deep network model to be used for respectively performing replication and sampling operation based on curvature on initial eigenvectors extracted from the first number of sparse input points to obtain a second number of intermediate eigenvectors, performing splicing operation on each intermediate eigenvector, inputting the spliced intermediate eigenvectors into a multilayer perceptron, and determining sampling prediction points based on the sampling eigenvectors output by the multilayer perceptron; training the deep network model until an objective function determined by the sampling prediction points and the dense input points converges; and testing the deep network model to obtain point cloud data of an object under test after up-sampling.

Abstract: Methods and system for creating an infrared effect that can survives copying, can involve providing a metameric pair of pattern inks, wherein a first pattern ink reflects higher in an infrared spectrum as compared to a second pattern ink among the metameric pair of pattern inks, wherein the second pattern ink is less reflective than the first pattern ink. For the second pattern ink that is less reflective than the first pattern ink, a pattern can be created for the second pattern ink that is larger and less scattered than an existing design for a pattern ink. A color of media can be used as a common color for the metameric pair of patterns and inks to create an infrared effect from the metameric pair of pattern inks that survives copying on the media.

Abstract: Accurately detection of logos in media content on media presentation devices is addressed. Logos and products are detected in media content produced in retail deployments using a camera. Logo recognition uses saliency analysis, segmentation techniques, and stroke analysis to segment likely logo regions. Logo recognition may suitably employ feature extraction, signature representation, and logo matching. These three approaches make use of neural network based classification and optical character recognition (OCR). One method for OCR recognizes individual characters then performs string matching. Another OCR method uses segment level character recognition with N-gram matching. Synthetic image generation for training of a neural net classifier and utilizing transfer learning features of neural networks are employed to support fast addition of new logos for recognition.

Abstract: An image processing apparatus comprises a first acquisition unit configured to acquire a first image obtained by scanning a first printed material printed based on print data, a second acquisition unit configured to acquire one or more second images obtained by scanning a second printed material printed based on the print data, and a generation unit configured to generate an image obtained from the first image and at least one second images among the one or more second images acquired by the second acquisition unit, as a reference image to be compared with a third image obtained by scanning a third printed material printed based on the print data in order to inspect presence or absence of a defect in the third image.

Abstract: Techniques and systems are provided for positioning mixed-reality devices within mixed-reality environments. The devices, which are configured to perform inside out tracking, transition between position tracking states in mixed-reality environments and utilize positional information from other inside out tracking devices that share the mixed-reality environments to identify/update positioning of the devices when they become disoriented within the environments and without requiring an extensive or full scan and comparison/matching of feature points that are detectable by the devices with mapped feature points of the maps associated with the mixed-reality environments. Such techniques can conserve processing and power consumption that would be required when performing a full or extensive scan and comparison of matching feature points. Such techniques can also enhance the accuracy and speed of positioning mixed-reality devices.

Abstract: The present disclosure relates to systems and methods for processing real-time video and detecting objects in the video. In one implementation, a system is provided that includes an input port for receiving real-time video obtained from a medical image device, a first bus for transferring the received real-time video, and at least one processor configured to receive the real-time video from the first bus, perform object detection by applying a trained neural network on frames of the received real-time video, and overlay a border indicating a location of at least one detected object in the frames. The system also includes a second bus for receiving the video with the overlaid border, an output port for outputting the video with the overlaid border from the second bus to an external display, and a third bus for directly transmitting the received real-time video to the output port.

Abstract: Methods and devices for improving indicia decoding with an imaging device are disclosed herein. An example method includes: (a) searching, by an imaging device, a search region within a current image for an indicia, wherein the search region includes a plurality of search seeds; (b) attempting, by the imaging device, to decode the indicia within the search region by analyzing image data corresponding to each seed of the plurality of search seeds; (c) responsive to not decoding the indicia, capturing, by the imaging device, a subsequent image featuring the indicia; (d) adjusting, by the imaging device, the search region based on a distance between the imaging device and the indicia featured in the subsequent image; (e) designating the subsequent image as the current image; and (f) iteratively performing (a)-(f) until the imaging device decodes the indicia.

Abstract: An example apparatus includes at least one processor circuitry to execute or instantiate instructions to identify a media file is scheduled to be accessed by a media device within a first time period after a publishing of the media file was published by a media provider; select a first symbol to be inserted at a first symbol position and a second symbol to be inserted at a second symbol position to identify an access of the media file is to be accessed by the media device within the first time period, the first symbol position in a first bit sequence, the second symbol position in a second bit sequence; encode the first bit sequence in the media file on a first encoding layer of a multilayered watermark, and encode the second bit sequence in the media file on a second encoding layer of the multilayered watermark.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to encrypt media for identification. An example apparatus includes a mesh generation controller to generate a mesh based on an encryption matrix; an overlap controller to eliminate overlapping ones of edge connections of the mesh; an edge labelling controller to generate random labels for the edge connections based on a number of remaining ones of the edge connections of the mesh; an encrypted value controller to generate encrypted values based on the random labels; and an encryption controller to encrypt an input matrix with the encrypted values to enable identification of the input matrix.

Abstract: Example gesture matching mechanisms are disclosed herein. An example machine readable storage device or disc includes instructions that, when executed, cause programmable circuitry to at least: prompt a user to perform gestures to register the user, randomly select at least one of the gestures for authentication of the user, prompt the user to perform the at least one selected gesture, translate the gesture into an animated avatar for display at a display device, the animated avatar including a face, analyze performance of the gesture by the user, and authenticate the user based on the performance of the gesture.

Abstract: To perform 3-dimensional interpolation, a 3-dimensional model of an input text character is generated. For example, a 2-dimensional character may be given depth using an extrusion transformation. The 3-dimensional model of the input text character is compared to 3-dimensional models of candidate characters and the results of the 3-dimensional comparisons are used to select the optical character recognition (OCR) output for the input text character. The 3-dimensional comparison may be performed directly on the 3-dimensional models. Alternatively, a set of 2-dimensional images may be generated for each 3-dimensional model and 2-dimensional comparisons performed. By use of the additional information gathered from the comparisons of the 3-dimensional models, the correct OCR output character can be identified with greater confidence.

Abstract: Methods, apparatus, systems and articles of manufacture to monitor media are disclosed. An example apparatus includes memory; computer readable instructions; and processor circuitry to execute the computer readable instructions to: generate a plurality of errors by comparing (a) a plurality of watermarks adjusted by offsets and (b) reference data, the adjusted watermarks corresponding to watermark data with inaccurate timing information for media; identify an offset of the offsets based on the plurality of errors; and adjust timing information of a watermark of the watermarks using the offset to increase an accuracy of the timing information.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to monitor streaming media content. Example apparatus disclosed herein include means for determining whether a streaming media flag is asserted in a payload of a watermark detected in media presented by a media presentation device, the streaming media flag to indicate whether the media was distributed to the media presentation device as streaming media. Disclosed example apparatus also include means for discarding the detected watermark from collected data in response to a determination that the streaming media flag is asserted. Disclosed example apparatus further include means for reporting the collected data to a remote server via a network.

Abstract: A data processing system for generating a fingerprint of an image implements obtaining a first digital image; determining a first fingerprint for the first digital image comprising a first coarse-grain fingerprint element and a first fine-grain fingerprint element by determining the first coarse-grain component based on the first digital image; determining the first fine-grain component based on the first digital image; and generating the first fingerprint by combining the first coarse-grain component with the first-fine grain component; obtaining a second fingerprint for a second digital image, the second fingerprint comprising a second coarse-grain component and a second fine-grain component; comparing the first fingerprint with the second fingerprint to determine a similarity score; and performing one or more actions responsive to the similarity score equaling or exceeding a similarity threshold.

Abstract: Provided are a tour guiding method and apparatus, an electronic device and a storage medium. The method includes receiving a video stream collected by a user in a current location area of a target scenic spot and sent by an application device; determining, based on the collected video stream and prestored three-dimensional point cloud data of the target scenic spot, an augmented-reality-based content resource package corresponding to the current location area, where the augmented-reality-based content resource package includes at least six-degrees-of-freedom attitude data of the application device; and sending the augmented-reality-based content resource package corresponding to the current location area to the application device to enable the application device to provide the augmented-reality-based content resource package corresponding to the front location area for the user.

Abstract: A method, computer program, and computer system is provided for point cloud coding. The method includes receiving, from a bitstream, data corresponding to a point cloud; obtaining from the data a first prediction residual of a first component from among a plurality of components of an attribute associated with the point cloud; reconstructing the first prediction residual; determining a predicted second prediction residual based on the reconstructed first prediction residual and at least one model parameter; obtaining a second prediction residual of a second component from among the plurality of components based on the predicted second prediction residual; reconstructing the second prediction residual; and decoding the data corresponding to the point cloud based on the reconstructed first prediction residual and the reconstructed second prediction residual.

Abstract: In one aspect, an example method includes (i) receiving, from a content-distribution system, video comprising a watermark; (ii) extracting the watermark from the video; (iii) based on the extracted watermark, determining a content-creation attribute of the video that indicates a process by which the video was created, wherein the determining comprises using the watermark to select the content-creation attribute from among a set of two or more content-creation attributes comprising organically-generated video and synthetically-generated video; and (iv) in response to determining the content-creation attribute of the video, causing a content-presentation device to perform an action.

Abstract: An information processing apparatus sets a color mode in place of a monochrome mode on condition that the monochrome mode and multiplexing of additional information on a print target image are set as print settings based on an input image data; generates, based on the input image data, color image data corresponding to printing in a color mode which represents a color of the monochromated print target image by a value of a color signal; performs, for the color image data generated by the generation unit, processing for multiplexing the additional information on the print target image; and causes a printing apparatus to print, in the color mode, a multiplexed image on which the additional information is multiplexed.

Abstract: A method for detection of modification of an item of content, the method comprising: obtaining, for the item of content, a respective first value of each attribute in a set of one or more attributes of the item of content, the set of one or more attributes selected such that, for each of one or more predetermined types of modification, said type of modification affects the value of at least one attribute in the set of one or more attributes; performing a watermark decoding operation on the item of content; and in response to the watermark decoding operation producing payload data from the item of content: determining that the one or more predetermined types of modification have not been applied to the item of content if, for each attribute in the set of one or more attributes, the respective first value for that attribute matches a respective second value for that attribute determined using the payload; or determining that a modification has been applied to the item of content if, for at least one attribute i

Abstract: Disclosed herein are methods and systems for visually identifying anomaly events, comprising an edge node configured for applying a limited resources classifier to a plurality of images captured by imaging sensor(s) deployed to monitor a certain scene relating to a certain area to classify object(s) detected in the images, applying a trained context based Machine Learning (ML) model to classification data generated by the limited resources classifier to compute an anomaly score for potential anomaly event(s) relating to the detected object(s) based on one or more contextual attributes associated with the certain scene and transmitting one or more of the images to a remote server in case the anomaly score exceeds a threshold. The remote server is configured to further apply high performance visual analysis tool(s) to visually analyze the received image(s) in order to identify the one or more potential anomaly events.

Abstract: A display apparatus and an image displaying method are provided. The display apparatus includes a display module and a driving circuit. The driving circuit is coupled to the display module and receives an input image. The driving circuit determines a watermark area and a non-watermark area of the display module according to watermark information, and at least one of the watermark area and the non-watermark area is alternately driven by a first gamma curve and a second gamma curve. A brightness difference percentage between the first gamma curve and the second gamma curve at a same grayscale value between 10% and 90% of a grayscale percentage is between 0.2 and 0.6.

Abstract: The pose of a wide-angle image is determined by dewarping regions of the wide-angle image, determining estimated poses of the dewarped regions of the wide-angle image and deriving a pose of the wide-angle image from the estimated poses of the of the dewarped regions. The estimated poses of the dewarped regions may be determined by comparing features in the dewarped regions with features in prior dewarped regions from one or more prior wide-angle images, as well as by comparing features in the dewarped regions with features in a point cloud.

Abstract: Examples of the present disclosure describe systems and methods for detecting and remediating compression artifacts in multimedia items. In example aspects, a machine learning model is trained on a dataset related to compression artifacts and non-compression artifacts. Input data may then be collected by a data collection module and provided to a pattern recognition module. The pattern recognition module may extract visual and audio features of the multimedia item and provide the extracted features to the trained machine learning model. The trained machine learning model may compare the extracted features to the model, and a confidence value may be generated. The confidence value may be compared to a confidence value threshold. If the confidence value is equal to or exceeds the confidence threshold, then the input data may be classified as containing at least one compression artifact. Remedial action may subsequently be applied (e.g., boosting the system with technical resources).

Abstract: A system for modeling risk of rail buckling in railroad infrastructure is presented. The system can receive a myriad of data related to railroad tracks and/or railroad operations, and weight the data using specially-designed weighting factors that can be unique to each data type. The weighted data can be transformed via specialized algorithms to generate location scores reflective of a risk isolated to a particular area. The system can further utilize additional specialized algorithms to elucidate how such isolated risk can be extrapolated from one location to another. The system can implement a multilayer approach, formulating one or more layers of risk models and aggregating such models into an overarching risk model that can more-accurately forecast risk of rail buckling in a railroad track.

Abstract: The present invention generally relates to system, method and graphical user interface for executing one or more tasks in dynamic data driven enterprise application. The invention includes creation of rules on a rule creation interface by one or more syntax from a rule creation syntax data library. The system of the invention is configured to identify optimum rule to process one or more tasks. The invention provides machine learning models driven rule engine for executing the tasks wherein an AI engine invokes dynamic conditions of the rules to execute the task.

Abstract: A system for training neural networks that predict the parameters of a human mesh model is disclosed herein. The system includes at least one camera and a data processor configured to execute computer executable instructions for: receiving a first frame and a second frame of a video from the at least one camera; extracting first and second features from the first and second frames of the video; inputting the sequence of frames of the video into a human mesh estimator module, the human mesh estimator module estimating mesh parameters from the sequence of frames of the video so as to determine a predicted mesh; and generating a training signal for input into the human mesh estimator module by using at least one of: (i) a depth loss module and (ii) a rigid transform loss module.

Abstract: An information processing device includes a displacement calculation means and a motion estimation means. The displacement calculation means acquires time-series images obtained by capturing images of a measurement target region of a structure supported by a supporting member. The displacement calculation means calculates a three-dimensional displacement of the measurement target region from the acquired time-series images. The motion estimation means estimates a motion of the supporting member in the structure based on the three-dimensional displacement of the measurement target region.

Abstract: A digital watermark analysis apparatus, comprising an image capturing unit for capturing a printed product where additional information is embedded by superimposing a pattern on an image to acquire a captured image, a calculation unit for calculating a spatial frequency characteristic of each small area in the captured image, a specifying unit for specifying an embedded signal strength and an embedding position of the additional information, a decision unit for deciding, based on the embedding position information and the embedded signal strength information, a position in the captured image of a marker detection area for detecting a marker as a reference position for acquiring the additional information, and an acquisition unit for detecting a marker in the marker detection area and acquiring the additional information in the captured image with reference to the detected marker.

Abstract: A system for generating a depth output for an image is described. The system receives input images that depict the same scene, each input image including one or more potential objects. The system generates, for each input image, a respective background image and processes the background images to generate a camera motion output that characterizes the motion of the camera between the input images. For each potential object, the system generates a respective object motion output for the potential object based on the input images and the camera motion output. The system processes a particular input image of the input images using a depth prediction neural network (NN) to generate a depth output for the particular input image, and updates the current values of parameters of the depth prediction NN based on the particular depth output, the camera motion output, and the object motion outputs for the potential objects.

Abstract: Methods and systems for generating an image quality metric are described. A reference and a test image are first converted to the ITP color space. After calculating difference images ?I, ?T, and ?P, using the color channels of the two images, the difference images are convolved with low pass filters, one for the I channel and one for the chroma channels (I or P). The image quality metric is computed as a function of the sum of squares of filtered ?I, ?T, and ?P values. The chroma low-pass filter is designed to maximize matching the image quality metric with subjective results.

Abstract: Methods and systems for analyzing an integrity of a roof covering are presented. An airflow may be directed over one or more shingles or other discontinuous roof covering materials by an airflow unit. A respective lift for each of the discontinuous roof covering materials may then be observed by an imaging unit, and an overall roof integrity rating may then be generated by the one or more processors based on the respective lift of the discontinuous roof covering materials.

Abstract: The invention provides artificial intelligence-enabled image recognition methods and systems for continuously training a computer system to accurately identify a surgical item in a tray using at least 100 randomly created 2-dimensional images of a 3-dimensional synthetic item having unique identifiers assigned to the images or item. The invention also provides an artificial intelligence-enabled image recognition method and system for use to determine whether surgical instruments are present or missing on a surgical tray, and, if applicable, identifying those missing. In one aspect, a server receives an image and analyzes the image with a deep convolutional neural network to classify the type of tray and then compares a list of items that should be on the tray to that which the computer recognizes on the tray to generate an output displayed to a user identifying the items present and/or missing.