Abstract: A method and a device for encoding/decoding an image according to the present invention may determine a reference region for intra prediction of a current block, derive an intra prediction mode of the current block on the basis of a predetermined MPM candidate group, and perform intra prediction on the current block on the basis of the reference region and the intra prediction mode.

Abstract: The present disclosure provides an image processing method and apparatus, and relates to the field of image processing, and in particular to the field of image annotation. An implementation is: obtaining an image to be processed including a target region to be annotated; in response to a first click on the target region, performing a first operation to expand a predicted region for the target region based on a click position of the first click; in response to a second click in a position where the predicted region exceeds the target region, performing a second operation to reduce the predicted region based on a click position of the second click; and in response to determining that a difference between the predicted region and the target region meets a preset condition, obtaining an outline of the predicted region to annotate the target region.

Abstract: System and methods for non-contact monitoring in vehicles are described. The systems and methods may use depth sensing cameras as part of the non-contact monitoring system. In some embodiments, depth data from at least one depth sensing device that has a field of view of at least part of the interior of the vehicle is received, wherein the depth data represents depth information as a function of position across the field of view. The depth data is then processed to obtain further information related to the occupant within the vehicle.

Abstract: A method and/or system for template agnostic document reader for automated extraction of data from documents is disclosed, wherein the kernel values are extracted from document image using which horizontal lines and vertical lines are determined in the document image. The horizontal lines are determined by extracting pixel values representing character width in the document image. The area of intersecting horizontal and vertical lines in the image is identified as tabular section and tabular data is extracted. The area in the document image with text and horizontal lines and absence of vertical lines are identified as forms section and forms data is extracted. The area in the document image without any horizontal lines and vertical lines and with similar line spacing are identified as paragraph section and paragraph data is extracted.

Abstract: A system includes a training server that in a training phase causes a custom neural network model for foliage detection to learn features related to foliage from a modified training dataset and further learn a color variation range of a predefined color associated with the features. A combination of the features related to foliage and the color variation range of the predefined color is utilized to obtain a trained custom neural network model that is deployed in a camera apparatus. The camera apparatus in the operational phase captures a new color image of an agricultural field, operates the trained custom neural network model to detect one or more foliage regions in the new color image in a real time or near real time, and operates at least one of a plurality of agricultural implements, based on the detected one or more foliage regions in the new color image.

Abstract: Physical object boundary detection techniques and systems are described. In one example, an augmented reality module generates three dimensional point cloud data. This data describes depths at respective points within a physical environment that includes the physical object. A physical object boundary detection module is then employed to filter the point cloud data by removing points that correspond to a ground plane. The module then performs a nearest neighbor search to locate a subset of the points within the filtered point cloud data that correspond to the physical object. Based on this subset, the module projects the subset of points onto the ground plane to generate a two-dimensional boundary. The two-dimensional boundary is then extruded based on a height determined from a point having a maximum distance from the ground plane from the filtered cloud point data.

Abstract: Estimating a head pose may include obtaining sensor data corresponding to a head and at least a portion of the body of a human subject and determining an estimate of a three-dimensional (3D) body pose using the obtained sensor data. The estimation can further include generating a first rendering of at least the human subject's head using the obtained sensor data and generating a plurality of head pose sample data sets by applying the estimated 3D body pose to a head-pose generative model. Further, the head pose estimation can include generating a plurality of second renderings respectively from each of the plurality of head pose sample data sets; determining which of the plurality of second renderings is closest to the first rendering; and selecting the second rendering determined to be closest to the first rendering.

Abstract: The present disclosure provides a system that searches for and finds orbital debris that can be a hazard to satellites and the like, for which the debris is sunlit. The system includes a ground-based telescope pointed at the sky; a detector array that detects images of the sunlit debris crossing the field of the detector; and a processing system that computes tracks from the detector data using a hierarchical algorithm, which builds longer tracks from previously computed shorter tracks, determines whether the computed tracks correspond to valid debris detections, and converts the track computations into debris brightness and debris orbital trajectory.

Abstract: Disclosed is a human motion capture method based on unsynchronized videos, which can effectively recover the 3D motion of a target person through multiple unsynchronized videos of the person. In order to utilize multiple unsynchronized videos, the present disclosure provides a video synchronization and motion reconstruction method. The present disclosure is implemented in the following steps: synchronizing multiple videos based on a 3D human pose; performing motion reconstruction based on synchronized videos, modeling the motion difference across different viewpoints by using the low-rank constraint to realize high-precision human motion capture from the plurality of unsynchronized videos. According to the present disclosure, more accurate motion capture is carried out by using multiple unsynchronized videos.

Abstract: The present invention discloses a cardiac transmembrane potential reconstruction method based on a graph convolutional neural network and an iterative threshold contraction algorithm. The cardiac transmembrane potential is econstructed iteratively through the iterative threshold contraction algorithm embedded in the graph convolutional neural network, and the graph convolutional neural network is used to extract the correlation information between nodes in the non-Euclidean dat a of the cardiac transmembrane potential, while retaining the rigorous mathematical calculations of the iterative threshold contraction algorithm, a solution og the cardiac transmembrane potential is obtained after multiple iterations.

Abstract: An apparatus for provisioning assistance to users in performing activities. The apparatus includes a drone configured to be at least one of positioned and moved to at least one of a plurality of positions, an imaging sensor coupled to the drone, and configured for imaging an environment of the drone based on at least one of the positioning and the moving of the drone, a processing device coupled to the drone, and communicatively coupled with the imaging sensor, and a device coupled with the drone, and operatively coupled with the processing device. The processing device is configured for generating an imaging data based on the imaging, analyzing the imaging data using a machine learning model, generating an insight associated with an activity based on the analyzing, and determining an operation based on the insight. The device is configured for performing the operation.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for monocular underwater camera biomass estimation. In some implementations, an exemplary method includes obtaining an image of a fish captured by an underwater camera; identifying portions of the image corresponding to one or more areas of interest; extracting the portions of the image from the image; providing the portions of the image to a model trained to detect objects in the portions of the image; and determining an action based on output of the model indicating a number of object detections.

Abstract: A device for categorising regions in images is disclosed. The device comprising: an input for receiving a first set of images, and defining one or more regions of for each image of the first set of images and a categorisation for the one or more regions, and a second set of images, and a categorisation for each image of the second set; and a processor configured to train a first machine learning algorithm to categorise features in images by: processing the images of the first and second set using the first algorithm to estimate feature regions in the images and a categorisation for each of the feature regions, and training the first algorithm in dependence on the categorisations received for the images of the first and second sets.

Abstract: Noise preserving models and methods for resolution recovery of x-ray computed tomography (e.g., using a computerized tool) are enabled. For example, a system can comprise: a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise: a pair generation component that generates a pair of images, the pair of images comprising an input image and a ground truth image, a training component that trains a machine learning based sharpening algorithm by approximately minimizing a loss function that determines an error between a sharpened image and the ground truth image, and a sharpening component that, using the sharpening algorithm, sharpens the input image to generate the sharpened image, wherein the sharpened image comprises a second noise that is similar in intensity to a first noise of the input image.

Abstract: An automatic video production device that performs fitting or fusion processing of a predetermined child video object that is not included in a parent video into a predetermined video scene of the parent video content as a video fusion source, the automatic video production device including a video content interpreting unit that interprets the entirety or a part of the video content of the parent video content, or divides the parent video content into a predetermined parent video scene to generate processing data that is predetermined parent video interpretation data obtained by converting a content interpretation result of the parent video or a division result of the parent video scene into data in a predetermined description format.

Abstract: A computing system implementing a physical verification tool can identify edges of a geometric pattern located within a search area surrounding a point of interest in a semiconductor layout design, characterize the edges of the geometric pattern based on locations of center points of the edges from the point of interest within the search area, and generate geometrical feature vectors for the point of interest in the semiconductor layout design based on the characterization of the edges of the geometric pattern. The computing system can reconstruct the semiconductor layout design corresponding to the search area surrounding the point of interest using the geometrical feature vectors for the point of interest in the semiconductor layout design.

Abstract: Methods, systems, and apparatus, including medium-encoded computer program products, for a secure edge platform that uses image classification machine learning models. An edge platform can include at least one camera and can identify image classification models that generate classification output data from image data generated by the cameras. The edge platform can receive image data generated by the camera, and provide the image data to the models. In response to providing the image data classification models, the edge platform can receive classification output data. In response to receiving the classification output data from the image classification models, the edge platform can generate augmentation data that is associated with the image data, then transmit detection data to a central server platform. The detection data can include (i) the classification output data and (ii) the augmentation data associated with the image data. Data can be made recordable, reportable, searchable, and alarmable.

Abstract: A method (400) and a system (200) for generating a chromatically modified image of one or more components on a microscopic slide (303) is disclosed. In one aspect of the invention, the method includes obtaining the image of the one or more components on the microscopic slide (303). Additionally, the method (400) includes processing the image to identify the one or more components. The method (400) further includes segmenting at least one part of the one or more components identified from the image. Furthermore, the method (400) includes chromatically modifying the at least one part of the one or more components and generating a chromatically modified image of the one or more components.

Abstract: An image processing device includes: a determination means for determining an image capturing means used for capturing at least one particular portion in a combined image in which a first partial image captured using a first image capturing means and a second partial image captured using a second image capturing means are stitched together; and a correction means for applying image correction to the combined image based on a determination result of the determination means.

Abstract: An information processing device of the present invention includes a detection means that detects the content of an image, a determination means that determines a processing mode for the image based on the result of detection of the content of the image, and an execution means that executes processing for a captured image corresponding to the processing mode.