Abstract: Tracking system for tracking one or more reflective markers includes at least two optical sensors configured to obtain image data of an environment that includes at least one marker. The tracking system obtains the image data from the at least two optical sensors. The tracking system is configured for extracting, from the image data, optical signatures representing reflections of the optical signal from at least one marker, determining optical centroids of the optical signatures of the at least one marker, estimating an initial pose for at least one marker, determining offset error vectors from the optical centroids of the at least one marker based on the initial pose, determining corrected optical centroids based on the offset error vectors and the optical centroids, and determining a corrected three dimensional position of the marker in the environment based on the corrected optical centroids of the marker.

Abstract: A learning device is configured to acquire first training data that is training data regarding a registered category object and second training data regarding an unregistered category object, the registered category object belonging to a registered category which is registered as an identification target, the unregistered category object not belonging to the registered category. The learning device is also configured to calculate, on a basis of the first training data and the second training data, an identification score indicating a degree of certainty that an object to be identified belongs to the registered category. The learning device is also configured to calculate, on a basis of the second training data, an unregistered score indicating a degree of certainty that the object to be identified does not belong to the registered category.

Abstract: Implementations are described herein for automatically labeling synthetic plant parts in synthetic training images, where the synthetic training images and corresponding labels can be used as training data for training machine learning models to detect, segment, and/or classify various parts of plants in digital images. In various implementations, a digital image may be obtained that captures an area. The synthetic training image may be generated to depict one or more three-dimensional synthetic plants in the area. In many implementations, a plant mask, identifying individual plants as a whole in the synthetic training image, as well as a part mask, uniquely identifying one or more parts of the synthetic plant models, can be overlaid on the synthetic training image to label the one or more parts of the synthetic plant models.

Abstract: An example device for decoding point cloud data includes: a memory configured to store point cloud data; and one or more processors implemented in circuitry and configured to: decode a frame of the point cloud data including a plurality of points, each of the points being associated with position values defining a respective position of the point; determine a global scaling factor for the frame; and scale the position values of each of the points by the global scaling factor. The scaling may be clipped to prevent the points exceeding the boundaries of a corresponding bounding box including respective points.

Abstract: A distance measurement device includes: an image capturer that captures N segmental images corresponding to N segmental distances into which a distance measurement range is divided; and a range image generator that generates a range image from the N segmental images. The range image generator determines: among segmental pixels included in the N segmental images, a segmental pixel having a maximum signal value from N segmental pixels at the same pixel position among pixel positions; a value indicating a segmental distance of the segmental pixel having the maximum signal value to be a distance value of the pixel position of the range image, when the maximum signal value is greater than or equal to a threshold; and a value indicating a value outside the distance measurement range to be the distance value of the pixel position of the range image, when the maximum signal value is less than the threshold.

Abstract: The present disclosure provides a computer-implemented method for correlating at least one infrared 2D-image to a 3D-representation of at least a part of a tooth displayed in a graphical user-interface, of a hand-held scanning device, on a screen, comprising the steps of: obtaining a first set of 2D-images of the at least part of the tooth; forming a 3D-representation of the at least a part of the tooth from the first set of 2D-images; displaying, in the graphical user-interface, the 3D-representation; obtaining a second set of 2D-images, wherein the second set of 2D images are infrared 2D-images acquired within the at least part of the tooth; displaying, in the user-interface, at least one of the 2D-images from the second set of 2D-images; displaying, in the user-interface, a manipulator configured to change between 2D-images in the second set of 2D-images.

Abstract: Disclosed are an image processing method and device using a line-wise operation. The image processing device, according to one embodiment, comprises: a receiver for receiving an image; a first convolution operator for generating a feature map by performing a convolution operation on the basis of the image; and a compressor for compressing the feature map into units of at least one line; and a decompressor for reconstructing the feature map compressed into units of lines.

Abstract: Disclosed herein is a method for managing item recommendation using a degree of association between language units and usage history to manage recommendation of similar items with high probability of purchase, rather than a matching method expressed by keywords, recommendation management, by adding or deleting experience items using a vector model-based reasoning method based on a word-to-word association, in a scheme of planning a novel recognition system through the study of human emotions and tastes, T.P.O (Time, Place, Occasion) and various list-specific characteristics (color, texture, etc.) based on the language used in everyday life in consideration of language units and items preferred or experienced and/or purchased by a user, and of applying machine learning technology and natural language understanding technology.

Abstract: An image analysis system including at least one processor and at least one memory is provided. The image analysis system is configured to receive image data associated with a brain of a patient, the image data including a first three-dimensional (3D) diffusion weighted imaging (DWI) image acquired using a magnetic resonance imaging (MRI) system and a second 3D DWI image, concurrently provide the first 3D DWI image to a first channel of a trained model and the second 3D DWI image to a second channel of the trained model, receive an indicator associated with the first 3D DWI image and the second 3D DWI image from the model, generate a report based on the indicator, and cause the report to be output to at least one of a memory or a display.

Abstract: Disclosed are an image processing method and device using a line-wise operation. The image processing device, according to one embodiment, comprises: a receiver for receiving an image; a first convolution operator for generating a feature map by performing a convolution operation on the basis of the image; and a compressor for compressing the feature map into units of at least one line; and a decompressor for reconstructing the feature map compressed into units of lines.

Abstract: A three-dimensional image transformation, executing on one or more computer systems, can mathematically transform a first two-dimensional image space onto a second two-dimensional image space using a three-dimensional image space. The three-dimensional image transformation can project the three-dimensional image space onto the first two-dimensional image space to map the first two-dimensional image space to the three-dimensional image space. Thereafter, the three-dimensional image transformation can project the second two-dimensional image space onto the three-dimensional image space to map the three-dimensional image space to the second two-dimensional image space.

Abstract: A method of joint denoising and demosaicing using a neural network to generate an output image and to a computing device for implementing the method is provided. The method includes obtaining image data collected by a color filter array (CFA), and jointly performing denoising and demosaicing on the CFA image data using a trained neural network to generate an output image, wherein the neural network has a lightweight U-Net architecture and is trained on a plurality of pairs of training images. One image in each pair of training images is obtained with a lower ISO value than another image in the pair of training images, and is processed by a processing algorithm (image signal processor (ISP)), and the other image in each pair of training images is in a format of CFA image data.

Abstract: A unibody transtibial prosthetic device includes a socket personalized for a specific patient's residual limb. A pylon extends from the socket, the pylon being a unitary polymer structure of interconnected elongated supports having open spaces therebetween. The device also includes a foot-ankle complex, the foot-ankle complex being a unitary polymer extending from the pylon, the foot and ankle unitary structure being shaped to provide multi-axial dynamic flex to enable dorsiflexion, plantar flexion, inversion and eversion motion for smooth symmetric gait performance and energy capture and return. The socket, pylon and foot-ankle complex are portions of a unibody.

Abstract: A method for generating a high-dynamic-range (HDR) image includes (a) denoising a short-exposure-time image, wherein the denoising comprises applying a first guided filter to the short-exposure-time image, the guided filter utilizing a long exposure-time-image as its guide, (b) after the step of denoising, scaling at least one of the short-exposure-time image and the long-exposure-time image to place the short-exposure-time image and the long-exposure-time image on a common radiance scale, and (c) after the step of scaling, merging the short-exposure-time image with the long-exposure-time image to generate the HDR image.

Abstract: A maintenance support system includes a network interface, a memory, and a processor configured to, upon receipt of first information indicating a status of a first apparatus via the network interface, store the first information in the memory, upon receipt of second information indicating a status of a second apparatus via the network interface, store the second information in the memory, and determine a priority of on-site maintenance between the first and second apparatuses based on the first and second information stored in the memory.

Abstract: One or more computer processors establish a geofence surrounding a display having a plurality of pixels capable of change based on one or more display capabilities. The one or more computer processors monitor for a change in at least one pixel of the plurality of pixels. The one or more computer processors identify a photosensitive user within the established geofence. The one or more computer processors responsive to the at least one pixel change associated with the display, calculate a photosensitivity score utilizing a model trained for one or more photosensitive conditions associated with the photosensitive user. The one or more computer processors adjust the display to show a change on the at least one pixel based on the calculated photosensitivity score.

Abstract: A method of controlling a communication terminal including a near-field communication unit includes setting, as operation settings of the communication terminal, whether to enable wireless communication functions by the near-field communication unit and controlling to display a predetermined notification before displaying a screen for performing a login request upon condition that a user operation to transition to a screen for performing a login request to an external device has been received, and that settings have not been made in the setting of the communication terminal at least to enable wireless communication functions by the near-field communication unit as operation settings of the communication terminal.

Abstract: Image processing unit is provided in computer, and performs: for each of input images constituting a moving image obtained by capturing a workpiece during arc welding, a spatter detection step of detecting a spatter from an input image constituting a moving image of the workpiece, the moving image being generated by capturing the workpiece during the arc welding; a background bright spot identification step of identifying, as a background bright spot, a position in the moving image, the position being a position where a number of times of the detection in the spatter detection step is equal to or more than a predetermined reference number of times; and a spatter number identification step of identifying, for one input image, a number of spatters excluding spatters each corresponding to the background bright spot identified by the background bright spot identification step among the spatters detected by the spatter detection processing.

Abstract: A feature information acquisition unit acquires the first feature information on the first medical image and second feature information on the second medical image having an imaging time different from an imaging time of the first medical image. A sentence creation unit compares the first feature information and the second feature information generated by the feature information acquisition unit, and creates a sentence representing a change between the first medical image and the second medical image. A display control unit causes the display unit to display a sentence representing a change.

Abstract: A server device includes communication means, information storage means, and output means. The communication means communicates with an information processing device that includes a display unit for displaying a symbol and a sending unit for sending information relating to the failure of the own device. The information storage means stores the information relating to the failure sent from the information process device. The output means outputs information relating to the failure stored in an access destination specified by the symbol to a user terminal that reads the symbol.