Abstract: A method and system for tracking movements of objects in a sports activity are provided. The method includes matching video captured by at least one camera with sensory data captured by each of a plurality of tags, wherein each of the at least one camera is deployed in proximity to a monitored area, wherein each of the plurality of tags is disposed on an object of a plurality of monitored objects moving within the monitored area; and determining, based on the video and sensory data, at least one performance profile for each of the monitored objects, wherein each performance profile is determined based on positions of the respective monitored object moving within the monitored area.

Abstract: Systems, methods, tangible non-transitory computer-readable media, and devices associated with object association and tracking are provided. Input data can be obtained. The input data can be indicative of a detected object within a surrounding environment of an autonomous vehicle and an initial object classification of the detected object at an initial time interval and object tracks at time intervals preceding the initial time interval. Association data can be generated based on the input data and a machine-learned model. The association data can indicate whether the detected object is associated with at least one of the object tracks. An object classification probability distribution can be determined based on the association data. The object classification probability distribution can indicate a probability that the detected object is associated with each respective object classification. The association data and the object classification probability distribution for the detected object can be outputted.

Abstract: This method for encoding a 3D point cloud comprises: —segmenting the point cloud into first patches (2); —determining inverse projection parameters of the patches (4); —projecting the first patches to planes using the inverse projection parameters (10); —encoding the planes (12); —determining sparse points in the point cloud not belonging to any patch (HC, 18); and—encoding the sparse points using an octree-decomposition (20).

Abstract: According to one embodiment, a medical image diagnostic apparatus includes processing circuitry. The processing circuitry inputs a noise correlation map and a medical image or an intermediate image to a learned model that is functioned to generate a denoise image, in which noise of the medical image or noise of the intermediate image is reduced, based on the medical image generated based on data collected with respect to a subject or the intermediate image at a front stage for generating the medical image and the noise correlation map correlated with the noise included in the medical image or the intermediate image, and generates the denoise image, in which the noise of the medical image or the noise of the intermediate image is reduced.

Abstract: Disclosed in the embodiments of the present application are method and apparatus for identifying damaged part of vehicle, server, client and system. The method comprises: pre-establishing identifiable vehicle feature library including vehicle parts and feature correspondence library including relative positional relationships of these parts. During the loss assessment image capturing procedure, the user manually delineates the damage location on the client. The identifiable vehicle features in the image can be identified by the server, the relative positions of the identifiable features and the mark delineated by user are determined according to these identifiable features.

Abstract: This disclosure provides an image recommendation method, a client, a server, a computer system and a medium. The method includes acquiring an image, sending the acquired image to a server, such that the server extracts a scale invariant feature of the acquired image and performs retrieval of identical images according to the scale invariant feature of the acquired image, and such that the server extracts a multi-scale feature of the acquired image and performs retrieval of similar images according to the multi-scale feature of the acquired image, and receiving at least one recommended image. The at least one recommended image is based on result of the identical image retrieval and result of the similar image retrieval.

Abstract: An enhanced imaging system for a motor vehicle includes a vision processing module that generates a data signal, in response to the camera capturing at least one of the video and the image. A graphics processor is configured to tone map the video or image to generate an RGB histogram including an overall tonal range. The processor is further configured to compare the overall tonal range to a tonal threshold. The processor detects one or more objects having a boundary that separates an interior region having an object tonal value from an exterior region having an exterior tonal value. The processor generates an optimized signal for increasing a difference between the object tonal value and the exterior tonal value, in response to the overall tonal range being above the tonal threshold. The system can further include a display device for displaying an optimized video or image.

Abstract: System and methods are provided for improved visual search systems that can use local features of images. The search system provides a user interface that enables a user to select areas or portions of an image to search on the selected features and the overall appearance of the image. The search system further provides customized user interfaces to exclude certain portions of images from the search algorithms. The search system can be used to detect potential intellectual property risks associated with items in an electronic catalog.

Abstract: A method of generating neural network training image annotations includes training a first neural network to identify and segment hands in images using a first set of 2D images with hand portions segmented in each image; substantially simultaneously capturing both a second set of 2D images, and a third set of images including depth images, depicting hands holding a particular type of object; correlating each of the second set of images with corresponding images of the third set to identify and segment foregrounds from backgrounds in the second set of images; applying the trained first neural network to the identified foregrounds to identify hand portions of the foregrounds and segment object portions from identified hand portions; and training a second neural network, using the segmented object portions of the second set of images as training data, to identify the particular type of object in new images.

Abstract: A method of operating a refrigerator, as provided herein, may include initiating a first image capture sequence at a camera module and identifying a first stored item based on a first two-dimensional image of the first image capture sequence. The method may further include determining an internal location of the first stored item within a chilled chamber or generating an expanded image of the first stored item and a second stored item spaced apart from the first stored item.

Abstract: An evaluation system includes: an acquisition unit that acquires an image acquired by imaging an exterior of a vehicle; and an evaluation unit that derives and assigns an evaluation point for evaluating social credibility of a vehicle occupant of the vehicle on the basis of the image acquired by the acquisition unit.

Abstract: Provided is an object detection device capable of accurately calculating a movement parameter related to the movement of an object. An object detection device (1) includes a feature extraction unit (2) and a calculation unit (4). When an object passes each of a plurality of irradiation areas of irradiation light from a first sensor and a second sensor, which are configured to detect a feature of a part of a surface of an object by applying irradiation light, the feature extraction unit (2) extracts features of the object in the plurality of irradiation areas. The calculation unit (4) calculates a movement parameter of the object between the plurality of irradiation areas when a difference between the features respectively extracted in the plurality of irradiation areas falls below a predetermined first threshold.

Abstract: A device configured to emulate an actor in a correlithm object processing system includes a memory and a processor. The memory stores an actor table that includes a string correlithm object comprising a plurality of sub-string correlithm objects. The actor is implemented by the processor and receives an input correlithm object, determines n-dimensional distances between the input correlithm object and at least a portion of the plurality of sub-string correlithm objects, and identifies a sub-string correlithm object from the actor table with the shortest determined n-dimensional distance. The actor outputs the real-world output value associated with the identified sub-string correlithm object in the actor table.

Abstract: A system and a method monitor a biological process. The method includes obtaining an abnormal tissue mask from an abnormal tissue segmentation of an image of an object containing tissue to be analyzed, the image being acquired at a time t0 being a reference time point. Other images of the object are registered onto the abnormal tissue mask, the other images being acquired at other time points. Image contrasts of the other images are normalized with respect to the contrasts of the image acquired at the reference time point. The normalized images are subtracted for each available contrast in order to obtain difference images. A joint difference image is created by summing the previously obtained difference images. A biological process progression map is created by overlapping the abnormal tissue mask obtained and the joint difference image after applying a pre-defined threshold.

Abstract: A weight-bearing stance corrected foot orthotic (12) is adapted to be used on the foot (2) of a anaesthetised patient in the supine or prone position, the weight bearing stance corrected foot orthotic (12) adapted to dorsiflex the toes of the forefoot of the patient an angle of between 30° to 50° to the plane of the foot (2). A surgical foot orthotic (12) is formed by the steps of disposing a patient's foot (2) or both feet in a weight bearing neutral position and dorsiflexing the forefoot or forefeet of the patient such that patient's foot (2) or feet are in or towards the Windlass configuration. A first orthotic (5) correcting the stance of the patient in the weight bearing position with dorsiflexed forefoot is formed and this is scanned to form an electronic image of the corrective load bearing surface.

Abstract: Generally, an information processing device according to one embodiment includes storage, a receiver, a detector, an extractor, and a position specifier. The storage stores therein, imaging positional information indicating, identification information on a landmark set, and registration landmark information, in association with one another. The receiver receives a captured image for position specification from an onboard device. The extractor extracts imaging landmark information serving as information on a detected landmark from the captured image for position specification. The position specifier specifies the position indicated by the imaging positional information associated with the identification information on the landmark set including the registration landmark information similar to the imaging landmark information as the position of a vehicle at time when the captured image for position specification is taken.

Abstract: An image processing apparatus includes an acquisition unit configured to acquire a plurality of continuous images, an extraction unit configured to extract a difference between two images among the plurality of continuous images, a first image processing unit configured to acquire a third image by removing a difference between portions smaller than a predetermined size from the difference extracted by the extraction unit, and a first combining unit configured to combine the two images by using the third image acquired by the first image processing unit. The image processing apparatus may implement the aforementioned units using a processor(s) that execute(s) a program of instructions stored in memory.

Abstract: Embodiments of systems and methods for detecting expected user intervention across multiple blades during a Keyboard, Video, and Mouse (KVM) session are discussed. In an embodiment, a chassis may include an Enclosure Controller (EC) coupled to a plurality of Information Handling Systems (IHSs) in a chassis, the EC comprising: a processor; and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the EC to: select a first IHS to initiate a first KVM session; register for a notification from the first IHS while the first IHS performs one or more operations; switch to a second IHS to initiate a second KVM session; and during the second KVM session, receive the notification.

Abstract: An image processing apparatus comprises an acquisition unit configured to acquire image data, a first tone correction unit configured to estimate transparency for each region of the image data, and correct tone, a second tone correction unit configured to correct tone of the image data using a tone curve, and a control unit configured to control which tone correction unit is to be used to perform tone correction.

Abstract: In some examples, a first set of image data is received, the first set of image data corresponding to images of a first type and being of a person in an environment of a vehicle and including a first plurality of images of the person over a time interval. In some examples, a second set of image data is received, the second set of image data corresponding to images of a second type and being of the person in the environment of the vehicle and including a second plurality of images of the person over the time interval. In some examples, the first set of image data and the second set of image data are processed to determine a recognized action of the person, which includes using a first neural network to determine the recognized action of the person.