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: An image processing method is provided for an electronic device. The method includes obtaining a target image comprising a target object; recognizing target two-dimensional location coordinates of the target object in the target image and a target attribute type corresponding to the target object; and obtaining a target three-dimensional point cloud associated with the target image. The method also include, according to a mapping relationship between the target three-dimensional point cloud and all pixels in the target image, obtaining three-dimensional location coordinates corresponding to pixels in the target two-dimensional location coordinates, as target three-dimensional location coordinates; determining a setting region in three-dimensional map data according to the target three-dimensional location coordinates; and setting the target attribute type for the target object in the setting region. Electronic device and non-transitory computer-readable storage medium counterparts are also contemplated.

Abstract: A position information acquisition device for acquiring position information of a position acquisition target arranged in a space includes a processor configured to detect light that is based on identification information included in-common in captured images that are images of the space captured from a plurality of shooting directions that are different from each other, acquire a three-dimensional position in the space of the position information acquisition target identified by the identification information, based on detection positions of the detected light in the captured images, and position information of image capturing devices during capturing performed by the image capturing devices, acquire reliability degree information of the acquired three-dimensional position of the position information acquisition target, based on information relating to an imaging state of each image capturing device during capturing of the captured images, and store the acquired the reliability degree information in a storag

Abstract: A medical image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured to obtain feature values related to the shape and a property of the heart. The processing circuitry is configured to estimate, by using the feature values, a state of the heart after a chest is opened. The processing circuitry is configured to estimate, based on a result of the estimation of the state of the heart, a state of the heart after the chest is closed after a treatment is completed. The processing circuitry is configured to output a parameter related to the estimated state of the heart after the chest is closed to a display.

Abstract: A method for estimating camera orientation relative to a ground surface. Line segments are detected from an image captured by a camera. A first virtual cube having three orthogonal vanishing points with a random 3D orientation is superimposed on to the image. The line segments of the image are classified grouped into 3D-directional groups. A second virtual cube is superimposed on to the image with an initial 3D orientation. An optimal 3D orientation of the second virtual cube is computed by iteratively changing the 3D orientation of the second virtual cube and measuring perpendicular distances of the three orthogonal vanishing points to the three line segment groups in each iteration starting with the initial 3D orientation, wherein the optimal 3D orientation of the second virtual cube being one that provides shortest perpendicular distances. Co-variances of the orthogonal vanishing points of the second virtual cube at the optimal orientation are computed.

Abstract: Implementations are described herein are directed to reconciling disparate orientations of multiple vision sensors deployed on a mobile robot (or other mobile vehicle) by altering orientations of the vision sensors or digital images they generate. In various implementations, this reconciliation may be performed with little or no ground truth knowledge of movement of the robot. Techniques described herein also avoid the use of visual indicia of known dimensions and/or other conventional tools for determining vision sensor orientations. Instead, techniques described herein allow vision sensor orientations to be determined and/or reconciled using less resources, and are more scalable than conventional techniques.

Abstract: A position estimation apparatus, a tracker, a position estimation method, and a program which enable estimation of the position or orientation of each of plural trackers in a common coordinate system are provided. A point cloud storage section (80) stores a common point cloud with positions expressed using a common coordinate system. A position estimation section (86) estimates the position or orientation of a first tracker in the common coordinate system on the basis of the common point cloud and first feature point data. The position estimation section (86) estimates the position or orientation of a second tracker in the common coordinate system on the basis of the common point cloud and second feature point data.

Abstract: A system and method include training of an artificial neural network to generate a simulated attenuation-corrected reconstructed volume from an input non-attenuation-corrected reconstructed volume, the training based on a plurality of non-attenuation-corrected volumes generated from respective ones of a plurality of sets of two-dimensional emission data and on a plurality of attenuation-corrected reconstructed volumes generated from respective ones of the plurality of sets of two-dimensional emission data.

Abstract: Compositing is provided in which visual elements from different sources, including live action objects and computer graphic (CG) merged in a constant feed. Representative output images are produced during a live action shoot. The compositing system uses supplementary data, such as depth data of the live action objects for integration with CG items and light marker detection data for device calibration and performance capture. Varying capture times (e.g., exposure times) and processing times are tracked to align with corresponding incoming images and data.

Abstract: According to one aspect, composite field based single shot trajectory prediction may include receiving an image of an environment including a number of agents, extracting a set of features from the image, receiving the image of the environment, encoding a set of trajectories from the image, concatenating the set of features and the set of trajectories from the image to generate an interaction module input, receiving the interaction module input, encoding a set of interactions between the number of agents and between the number of agents and the environment, concatenating the set of interactions and a localization composite field map to generate a decoder input, receiving the decoder input, generating the localization composite field map and an association composite field map, and generating a set of trajectory predictions for the number of agents based on the localization composite field map and the association composite field map.

Abstract: A system and method for taillight signal recognition using a convolutional neural network is disclosed. An example embodiment includes: receiving a plurality of image frames from one or more image-generating devices of an autonomous vehicle; using a single-frame taillight illumination status annotation dataset and a single-frame taillight mask dataset to recognize a taillight illumination status of a proximate vehicle identified in an image frame of the plurality of image frames, the single-frame taillight illumination status annotation dataset including one or more taillight illumination status conditions of a right or left vehicle taillight signal, the single-frame taillight mask dataset including annotations to isolate a taillight region of a vehicle; and using a multi-frame taillight illumination status dataset to recognize a taillight illumination status of the proximate vehicle in multiple image frames of the plurality of image frames, the multiple image frames being in temporal succession.

Abstract: The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

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: Various implementations disclosed herein include devices, systems, and methods for pose estimation using one point correspondence, one line correspondence, and a directional measurement. In various implementations, a device includes a non-transitory memory and one or more processors coupled with the non-transitory memory. In some implementations, a method includes obtaining an image corresponding to a physical environment. A first correspondence between a first set of pixels in the image and a spatial point in the physical environment is determined. A second correspondence between a second set of pixels in the image and a spatial line in the physical environment is determined. Pose information is generated as a function of the first correspondence, the second correspondence, and a directional measurement.

Abstract: The described positional awareness techniques employing sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to find new area to cover by a robot encountering an unexpected obstacle traversing an area in which the robot is performing an area coverage task. The sensory data are gathered from an operational camera and one or more auxiliary sensors.

Abstract: A system and method for documenting a scene having evidence markers is provided. The method includes placing the evidence markers in the scene. A plurality of 3D coordinates of points are measured on surfaces in the environment, a first portion of the plurality of 3D coordinates being on a first evidence marker of the evidence markers, the evidence marker having a photogrammetric symbol on one surface. A point cloud is generated from the plurality of 3D coordinates. The first evidence marker in the point cloud based is automatically identified at least in part on the photogrammetric symbol. The location and at least one attribute of the evidence marker are stored.

Abstract: A deposit detection device according to an embodiment includes a detection module and a determination module. The detection module detects a deposit region including a deposit adhering to a lens of an imaging device from a captured image captured by the imaging device. The determination module performs maintenance determination as to whether to maintain a detection history of detection by the detection module, based on brightness information of the captured image.

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: Systems and methods assessing the accuracy of at least one localization from a single molecule localization microscopy (SMLM) dataset containing a plurality of localizations are described. The systems and methods calculate a Wasserstein-induced flux (WIF) value indicative of a confidence in the accuracy of a localization within the SMLM data set.

Abstract: An orientation detection device obtains a detection information of a sensor that detects a displacement in the vertical direction occurring in the vehicle, computes a pitch angle of the vehicle on the basis of the detection information, obtains a gradient information indicating a gradient of a road on which the vehicle travels, and corrects a correlation between the detection information used in computation and the pitch angle on the basis of the gradient information.