Abstract: Embodiments disclose apparatus, methods and software for performing biological screening and analysis implemented using an instrument platform capable of detecting a wide variety of cell-based secretions, expressed proteins, and other cellular components. The platform may be configured for simultaneous multiplexed detection of a plurality biological components such that a large number of discrete samples may be individually sequestered and evaluated to detect or identify constituents from the samples in a highly parallelized and scalable manner.

Abstract: A medical image diagnostic apparatus includes a marker to be placed on a subject, at least one imaging unit configured to capture images of the subject and the marker, and a detection unit configured to detect movement of the marker from the images captured by the imaging unit. The marker includes a plurality of planar structures that can be detected by the detection unit, and the planar structures are spaced apart from each other with a distance no less than a predetermined distance.

Abstract: A method, an apparatus, an electronic device, and a computer-readable storage medium for detecting a wind turbine blade based on drone aerial photography are provided. The method includes: determining first initial three-dimensional position coordinates and a posture of a wind turbine; determining second initial three-dimensional coordinates of a first expected position with respect to a front shooting position of the wind turbine, based on the first initial three-dimensional position coordinates, the posture, and a preset distance; inputting the second initial three-dimensional coordinates of the first expected position into a flight control system of the drone, and controlling the drone to fly to the second initial three-dimensional coordinates based on a GPS system; and controlling the drone to track at least one first key point of blades of the wind turbine, and determining a three-dimensional movement trajectory of the first key point in a camera coordinate system.

Abstract: An image acquisition unit (110) acquires an image of an area around a mobile object as image data (31). A point cloud acquisition unit (120) acquires depth point cloud data (32) representing a depth, which is a distance to an object existing in the area around the mobile object, by a point cloud. A generation unit (140) calculates a depth to a position represented by a pixel included in the image data (31), using the image data (31) and the depth point cloud data (32), and generates high-resolution point cloud data (35) in which the calculated depth is added to the pixel included in the image data (31). An estimation unit (150) estimates a movement amount of the mobile object, using the high-resolution point cloud data (35).

Abstract: Embodiments of the present invention describe a system that receives an image depicting at least one subject, predicts at least one orientation keypoint associated with a section of the body part of the at least one subject via a neural network detector and determines a three-axis joint rotation associated with the section of the body part of the at least one subject based on at least one orientation keypoint associated with the body part of the at least one subject and at least one joint keypoint associated with the body part of the at least one subject. Orientation keypoints can improve the estimation of an associated joint keypoints, dense pose correspondence and landmark.

Abstract: A computer implemented method for determining an occupancy map in the vicinity of a vehicle comprises the following steps: successively acquiring sensor data of a sensor system, determining object detections based on the sensor data, overlaying the object detections in a spatial representation of the vicinity of the vehicle, defining, for an object detection of a first data acquisition process, an expectation area extending around the object detection, adjusting, if an object detection of a second data acquisition process is present within the expectation area, the position of the expectation area based on a difference between the position of the object detection of the first data acquisition process and the position of the object detection of the second data acquisition process, and removing an object detection of the expectation area from the occupancy map if no object detection can be determined in the expectation area for a predetermined number of successive data acquisition processes.

Abstract: A learning apparatus (500) according to the present invention includes a detection unit (510) that detects, as a candidate region of a learning target, a region detected by one of first detection processing of detecting an object region from a predetermined image and second detection processing of detecting a change region from background image information and the image, and not detected by the other, an output unit (520) that outputs at least a part of the candidate region as a labeling target, and a learning unit (530) that learns a model for performing the first detection processing or a model for performing the second detection processing by using the labeled candidate region as learning data.

Abstract: Techniques are described to estimate orientation of one or more cameras located on a vehicle. The orientation estimation technique can include obtaining an image from a camera located on a vehicle while the vehicle is being driven on a road, determining, from a terrain map, a location of a landmark located at a distance from a location of the vehicle on the road, determining, in the image, pixel locations of the landmark, selecting one pixel location from the determined pixel locations; and calculating values that describe an orientation of the camera using at least an intrinsic matrix and a previously known extrinsic matrix of the camera, where the intrinsic matrix is characterized based on at least the one pixel location and the location of the landmark.

Abstract: Disclosed herein is an improved method for identifying images containing objects-of-interest from a large set of images. The method comprises mixing two or more of the images to create a grouped image and exposing the grouped image to an object detector trained on grouped images to make an initial determination that the grouped image was formed from at least one image containing an object-of-interest. The images which formed the grouped image are then exposed to regular object detectors to determine a classification of the object-of-interest.

Abstract: Provided is a system, method, and computer program product for segmenting vessels in an ultrasound image. The method includes detecting edges of a vessel in the ultrasound image; detecting a vessel contour of the vessel in the ultrasound image based on the detected edges and a distance regularized level set evolution; and tracking the vessel contour with a Kalman Filter.

Abstract: In one example embodiment, a wound imaging system includes a user interface, a computer processor, and an active contouring module. The user interface is configured to display an image of a wound acquired by the wound imaging system and selectively receive inputs from a user defining an initial perimeter of the wound. An active contouring module is configured to operate on the computer processor to receive the inputs defining the initial perimeter of the wound, identify features of the image on opposing sides of the initial perimeter of the wound, and identify an actual perimeter of the wound based on the initial perimeter of the wound and the identified features. The user interface is further configured to display, on the image of the wound, the actual perimeter of the wound as identified by the active contouring module and selectively receive inputs from the user to modify the actual perimeter of the wound.

Abstract: An image processing device detects a spicula candidate region having a radial line structure from each of a plurality of tomographic images indicating a plurality of tomographic planes of an object and determines whether or not the spicula candidate region is a spicula on the basis of an amount of change of a center position of the line structure included in the spicula candidate region between the tomographic planes.

Abstract: According to one embodiment, a three-dimensional map estimation apparatus includes a processor that selects an imaging apparatus from a plurality of imaging apparatuses and then estimates a position and orientation for a moving object on which the selected imaging apparatus is mounted based on images captured by the selected imaging apparatus. The processor outputs a first position and orientation estimation result for the moving object based on images from selected imaging apparatuses. The processor calculates a second position and orientation estimation result indicating an estimated position and orientation for the moving object using the first position and orientation estimation result. The processor estimates a three-dimensional map for the surroundings of the moving object based on the second position and orientation estimation result.

Abstract: Systems and methods are disclosed for locating a retroreflective object in a digital image and/or identifying a feature of the retroreflective object in the digital image. In certain environmental conditions, e.g. on a sunny day, or when the retroreflective material is damaged or soiled, it may be more challenging to locate the retroreflective object in the digital image and/or to identify a feature of the object in the digital image. The systems and methods disclosed herein may be particularly suited for object location and/or feature identification in situations in which there is a strong source of ambient light (e.g. on a sunny day) and/or when the retroreflective material on the object is damaged or soiled.

Abstract: A method of efficiently and accurately computing a pose of an image with respect to other image information. The image may be acquired with a camera on a portable device and the other information may be a map, such that the computation of pose localizes the device relative to the map. Such a technique may be applied in a cross reality system to enable devices to efficiently and accurately access previously persisted maps. Localizing with respect to a map may enable multiple cross reality devices to render virtual content at locations specified in relation to those maps, providing an enhanced experience for uses of the system. The method may be used in other devices and for other purposes, such as for navigation of autonomous vehicles.

Abstract: A method and device for image processing, and storage medium are provided. In the method, an initial image I is acquired; a pixel I(i) of the initial image is selected; a transfer function ƒ is applied to the pixel I(i) to acquire a transferred pixel ?(i), and the transfer function ƒ is determined on the basis of at least the pixel information of the selected pixel; a predetermined tone-mapping function is applied to the transferred pixel ?(i) to acquire a tone-mapped transferred pixel ??(i); an inverse of the transfer function ƒ?1 is applied to the tone-mapped transferred pixel ??(i) to acquire a tone-mapped final pixel I?(i). Herein, the steps are repeated for a plurality of pixels of the initial image I to generate a final image I?, and for each of the plurality pixels the same tone-mapping function is applied.

Abstract: An analyzing apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires a plurality of time-series medical images. The processing circuitry calculates, for each of image pairs each formed of two medical images included in the medical images, a first index value indicating similarity between image signals in the two medical images. The processing circuitry also calculates, on the basis of a plurality of the first index values calculated for the respective image pairs, a second index value corresponding to a statistical value in a time direction of the first index values.

Abstract: In order to extract a feature suitable for comparison, the information processing device according to the present invention comprises: a prediction unit which, on the basis of the positional relationship between a plurality of objects detected and tracked in an input video and on the basis of the overlap between the plurality of objects, predicts the qualities of features extracted from the objects; a selection unit which selects, from among the plurality of objects, only those objects or that object for which the qualities of features predicted by the prediction unit satisfy a prescribed condition; and a feature extraction unit which extracts features from the objects or the object selected by the selection unit.

Abstract: In order to extract a feature suitable for comparison, the information processing device according to the present invention comprises: a prediction unit which, on the basis of the positional relationship between a plurality of objects detected and tracked in an input video and on the basis of the overlap between the plurality of objects, predicts the qualities of features extracted from the objects; a selection unit which selects, from among the plurality of objects, only those objects or that object for which the qualities of features predicted by the prediction unit satisfy a prescribed condition; and a feature extraction unit which extracts features from the objects or the object selected by the selection unit.

Abstract: In order to extract a feature suitable for comparison, the information processing device according to the present invention comprises: a prediction unit which, on the basis of the positional relationship between a plurality of objects detected and tracked in an input video and on the basis of the overlap between the plurality of objects, predicts the qualities of features extracted from the objects; a selection unit which selects, from among the plurality of objects, only those objects or that object for which the qualities of features predicted by the prediction unit satisfy a prescribed condition; and a feature extraction unit which extracts features from the objects or the object selected by the selection unit.