Abstract: An image recognition device and method retrieve information on a marker. The marker encodes information identifying an asset by encoding the information in a binary pattern as recesses and non-recesses in the marker. The image recognition is performed by imaging the marker, mapping contrast in the image, identifying variations in the contrast, creating a mesh overlaying the image, identifying the present or absence of recesses from the mesh, and reading the binary pattern represented by the recesses in the marker.

Abstract: Methods and systems for determining rotation and clipping parameters for images of unit load devices (ULDs) are disclosed herein. An example method includes capturing a set of image data featuring a ULD. The example method may further include locating a fiducial marker proximate to the ULD within the set of image data. The example method may further include cropping the set of image data, based upon the located fiducial marker, to generate a set of marker point data and a set of floor point data. The example method may further include rotating the set of image data based upon the set of marker point data and the set of floor point data, and clipping the rotated set of image data based upon the set of marker point data and the set of floor point data.

Abstract: Artificial intelligence using convolutional neural network with Hough Transform. In an embodiment, a convolutional neural network (CNN) comprises convolution layers, a Hough Transform (HT) layer, and a Transposed Hough Transform (THT) layer, arranged such that at least one convolution layer precedes the HT layer, at least one convolution layer is between the HT and THT layers, and at least one convolution layer follows the THT layer. The HT layer converts its input from a first space into a second space, and the THT layer converts its input from the second space into the first space. The CNN may be applied to an input image to perform semantic image segmentation, so as to produce an output image representing a result of the semantic image segmentation.

Abstract: The disclosed system may include a housing dimensioned to secure various components including at least one physical processor and various sensors. The system may also include a camera mounted to the housing, as well as physical memory with computer-executable instructions that, when executed by the physical processor, cause the physical processor to: acquire images of a surrounding environment using the camera mounted to the housing, identify features of the surrounding environment from the acquired images, generate a map using the features identified from the acquired images, access sensor data generated by the sensors, and determine a current pose of the system in the surrounding environment based on the features in the generated map and the accessed sensor data. Various other methods, apparatuses, and computer-readable media are also disclosed.

Abstract: Device, system, and method of computer vision, object tracking, and image analysis; particularly suitable or configured for analysis of images or videos of tennis. A device includes two adjacent and co-located cameras, oriented at an angle of 20 to 120 degrees relative to each other, capturing a combined field-of-view that covers at least 75 percent of an entirety of a tennis court. A processor analyzes the captured images or video using computer-vision algorithms, and detects a ball bounce event and its properties. Insights are generated with regard to the performance of one or more of the participating players.

Abstract: An information presentation system comprising an obtainment unit obtaining a feature of an object, a specification unit specifying the object from the feature, a display, a storage storing specification information and a communication unit communicating with an external server and obtaining related information of the object is provided. The specification unit specifies the object by searching for the specification information. The specification information includes a plurality of pieces of feature information observation targets and a plurality of pieces of object information which are associated with the plurality of pieces of feature information and related to the observation targets. The display displays the related information. In a case in which the specification unit has specified the object and there is a difference between the related information and the object information, the object information is updated based on the related information.

Abstract: Providing optical watermark signals for a visual authentication session by performing at least the following: receive, at an anti-spoof engine, an instruction to perform visual authentication operations for a visual authentication session, generate, with the anti-spoof engine, an optical watermark signal based on receiving the instruction, wherein the optical watermark signal includes at least one optical identifier to authenticate images captured during the visual authentication session, obtain, with the anti-spoof engine, an image source that includes captured images of the visual authentication session, determine, with the anti-spoof engine, whether the image source includes a reflected optical watermark signal, and compare, with the anti-spoof engine, whether the reflected optical watermark signal matches the generated optical watermark signal based on the determination that the image source includes the reflected optical watermark signal.

Abstract: Provided are an expression realization method and device for virtual character, and a storage medium, the method comprising: acquiring sequence frames of respective parts of a face of the virtual character, wherein the sequence frames of respective parts contain part sequences corresponding to respective expressions; acquiring a first part sequence corresponding to a first expression and a second part sequence corresponding to a second expression from the sequence frames of respective parts, wherein the first part sequence comprises a first transition part sequence, and the second part sequence comprises a second transition part sequence; and successively playing the first part sequence and the second part sequence according to a first preset instruction, wherein a playing of the first transition part sequence is located at a tail of the playing of the first part sequence, and a playing of the second transition part sequence is located at a head of the playing of the second part sequence.

Abstract: An identification apparatus includes processing circuitry configured to determine whether or not a first image and a second image are similar based on feature points extracted from each of the first image and the second image, and determine whether or not the first image and the second image are similar by comparing neighborhood graphs generated for each of the first image and the second image, the feature points being as nodes.

Abstract: A diagnostic support for a skin includes a radio-transparent structure that defines a folding surface of the skin and on which the skin may be stretched and consequently folded, thereby defining folded, mutually superimposed portions spaced apart from each other. The support may be used for radiographic inspection of a folded animal skin.

Abstract: A computer-implemented method for providing a vascular image data record includes receiving a plurality of projection-X-ray images recorded in temporal succession. The plurality of projection-X-ray images at least partially map a common examination region of an examination object. The plurality of projection-X-ray images map a temporal change in the examination region of the examination object. A change image data record is determined in each case based on at least one region of interest of the plurality of projection-X-ray images. The at least one region of interest includes a plurality of image points. The change image data record in each case includes a time-intensity curve for each of the image points. The vascular image data record is generated based on the change image data record, and the vascular image data record is provided.

Abstract: This application provides a method for detecting images of testing object using hyperspectral imaging. Firstly, obtaining a hyperspectral imaging information according to a reference image, hereby, obtaining corresponded hyperspectral image from an input image and obtaining corresponded feature values for operating Principal components analysis to simplify feature values. Then, obtaining feature images by Convolution kernel, and then positioning an image of an object under detected by a default box and a boundary box from the feature image. By Comparing with the esophageal cancer sample image, the image of the object under detected is classifying to an esophageal cancer image or a non-esophageal cancer image. Thus, detecting an input image from the image capturing device by the convolutional neural network to judge if the input image is the esophageal cancer image for helping the doctor to interpret the image of the object under detected.

Abstract: An unsupervised machine learning method with self-supervision losses improves a slice-wise spatial resolution of 3D medical images with thick slices, and does not require high resolution images as the ground truth for training. The method utilizes information from high-resolution dimensions to increase a resolution of another desired dimension.

Abstract: A liveness detection method and apparatus, and a facial verification method and apparatus are disclosed. The liveness detection method includes detecting a face region in an input image, measuring characteristic information of the face region, adjusting the measured characteristic information in response to the characteristic information not satisfying a condition, and performing a liveness detection on the face region with the adjusted characteristic information upon the measured characteristic information not satisfying the condition.

Abstract: There are provided a method for segmenting a sign language video by gloss to recognize a sign language sentence, and a method for training. According to an embodiment, a sign language video segmentation method receives an input of a sign language sentence video, and segments the inputted sign language sentence video by gloss. Accordingly, there is suggested a method for segmenting a sign language sentence video by gloss, analyzing various gloss sequences from the linguistic perspective, understanding meanings robustly in spite of various changes in sentences, and translating sign language into appropriate Korean sentences.

Abstract: In one aspect, a method for inspecting features of an image using an image inspection controller that includes a processor communicatively coupled to a memory is described. The method includes receiving, at the processor, an input image, performing, on the input image, one of a semantic segmentation process and an object classification process to generate an output image, and prompting a user to select between approving the displayed output image, and at least one of i) performing an additional semantic segmentation process on the displayed output image, and ii) performing an additional object classification process on the displayed output image.

Abstract: The present invention relates to a method and system for automatic localisation of static objects in an urban environment. More particularly, the present invention relates to the use of noisy 2-Dimensional (2D) image data to identify and determine 3-Dimensional (3D) positions of objects in large scale urban or city environments. Aspects and/or embodiments seek to provide a method, system, and vehicle for automatically locating static 3D objects in urban environments by using a voting-based triangulation technique. Aspects and/or embodiments also provide a method for updating map data after automatically new 3D static objects in an environment.

Abstract: A machine learning system, including at least one temporal filter. An input variable, encompassing a chronological sequence of images, is processed with the aid of the machine learning system, using the filter. The machine learning system is configured to use the filter on a sequence of pixels, which are all situated at identical coordinates of the images, or at identical coordinates of intermediate results. Filter coefficients of the filter are quantized. A method, a computer program, and a device for creating the machine learning system are also described.

Abstract: Techniques are generally described for generation of synthetic image data. In some examples, a selection of a first image may be received. The first image may depict at least a first object having a plurality of image attributes representing visual characteristics of the at least the first object. In some examples, a selection of a first image attribute of the plurality of image attributes to be maintained in subsequently-generated images may be received. In various examples, a first machine learning model may generate a second image having the plurality of image attributes. The change in an appearance of the first image attribute may be minimized in the second image while a change in the appearance of other attributes of the plurality of image attributes may be maximized in the second image.

Abstract: A method to assess a subject diagnosis is provided. The method includes receiving an image from an image-capturing device, the image comprising an area of interest in a test cartridge, and finding a border of the area of interest of the test cartridge and applying a geometrical transformation on an area delimited by the border of the test cartridge to bring the image of the area of interest in the test cartridge to a selected size and a selected shape. The method also includes identifying a target region within the area of interest of the test cartridge, evaluating a quality of the image based on a characteristic feature of the target region, and providing commands to adjust an optical coupling in the image-capturing device when the quality of the image is lower than a selected threshold.