Abstract: A computing system configured to identify a region of interest in an image having a plurality of pixels, each of which corresponds to a feature score. The region of interest is a section of the image where feature points reside. The computing system is also configured to traverse one or more pixels in the region of interest in a spiral sequence starting from a center of the region of interest to edges of the region of interest to determine whether the corresponding pixel is a feature point.

Abstract: An information management apparatus includes at least one processor configured to execute a program stored in a storage. The at least one processor acquires sequentially captured frames. The at least one processor acquires a movement state of a position of a light source in an imaging area, based on light source images contained in the acquired frames. The light source transmits information by means of light including an illumination pattern of the light. The at least one processor causes the storage to store the information and the movement state in association with each other.

Abstract: An image diagnosis assisting apparatus according to the present invention executes: processing of inputting an image of a tissue or cell; processing of extracting a feature amount of a tissue or cell from a processing target image; processing of extracting a feature amount of a tissue or cell from an image having a component different from that of the target image; and processing of determining presence or absence of a lesion and lesion probability for each of the target images by using a plurality of the feature amounts.

Abstract: Systems and methods are provided to perform context-aware text extraction.

Abstract: An object detection system capable of tracking a moving object over a wide range, at a high processing speed, and with a high accuracy of recognition without increasing the number of image capturing apparatuses installed in one place is provided. A movement information acquisition unit acquires movement information, which is information regarding a moving object included in a first image captured by a first image capturing apparatus among a plurality of image capturing apparatuses arranged in positions different from one another. A search range determination unit determines a limited search range in a second image captured by a second image capturing apparatus among the plurality of image capturing apparatuses in accordance with the movement information. An object recognition unit performs recognition of the moving object for the search range in the second image.

Abstract: Camera images may be utilized to detect substrate edges and provide information regarding the centering of the substrate within the fluid dispense system. Camera images may also be utilized to monitoring the location of a cup within the fluid dispense system. The signal processing techniques utilized may include data smoothing, analyzing only certain wavelengths of reflected energy, transforming the data (in one embodiment utilizing a Fourier transform), and/or analyzing a sub-set of the collected pixels of data. The camera image data collected herein may be combined with a wide variety of other data so as to better monitor, characterize and/or control a substrate processing process flow.

Abstract: In general, the subject matter described in this disclosure can be embodied in methods, systems, and program products for detecting motion in images. A computing system receives first and second images that were captured by a camera. The computing system generates, using the images, a mathematical transformation that indicates movement of the camera from the first image to the second image. The computing system generates, using the first image and the mathematical transformation, a modified version of the first image that presents the scene that was captured by the first image from a position of the camera when the second image was captured. The computing system determines a portion of the first image or second image at which a position of an object in the scene moved, by comparing the modified version of the first image to the second image.

Abstract: A method includes: recording an image at a sensor block, the sensor block; detecting a set of objects in the image based on an object classification model; generating a feature vector for the image based on the set of objects; accessing a workstation template for the work area, the workstation template defining a set of default objects for each workstation in the work area; identifying a subset of objects comprising an intersection of the set of default objects and the set of objects; removing the subset of objects from the feature vector; accessing an occupancy template for the work area, the occupancy template defining a set of significant objects; classifying the workstation as occupied based on the feature vector and the set of significant objects; and rendering a representation of the workstation at a work area interface, the representation indicating occupancy of the workstation.

Abstract: There is provided a method, system, and non-transitory computer-readable storage medium for classifying glints using an eye tracking system of a head-mounted device, by obtaining the position of any glint present in a current image of the first eye; obtaining a dataset indicative of the respective position of at least one glint detected in one or more previously captured images of the first eye; and, for each glint present in current image, determining if the position of the glint corresponds to the position of a glint in the dataset and, if the positions correspond, classify the glint as a static glint. The static glints may be excluded from further processing in the eye tracking system. If there has been a movement of an eye of the user of the head-mounted device, embodiments may further comprise updating the dataset based on the current image.

Abstract: Methods are disclosed for the generation and editing of layer delineations within three-dimensional tomography scans. Cross sections of a subject are generated and presented to an operator, who has the ability to edit layer delineations within the cross section, or determine parameters used to generate new cross sections. By guiding an operator through a set of displayed cross sections, the methods can allow for a more rapid, efficient, and error-free segmentation of the subject. The cross sections can be nonplanar in shape or planar and non-axis-aligned. The cross sections can be restricted to exclude one or more user-defined regions of the subject, or to include only one or more user-defined regions of the subject. The cross sections can be localized to a point-of-interest. Iterative implementations of the methods can be used to arrive at a segmentation deemed satisfactory by the user.

Abstract: An apparatus for predicting whether an object moving across a surface will reach a target destination is provided, the apparatus comprising circuitry configured to: receive a first image and one or more subsequent second images from a camera; identify a location of an object on a surface in the first image; identify a location of the object on the surface in one or more of the second images; determine one or more motion characteristics of the object based on the location of the object in the first image and the location of the object in the one or more second images; generate a predicted path of the object across the surface based on a model of the surface and the motion characteristics of the object; and generate a prediction of whether the object will reach the target destination based on the predicted path of the object and the location of the target destination.

Abstract: Described herein are a system and methods for generating a record of objects, as well as respective positions for those objects, with respect to a user. In some embodiments, a user may use a user device to scan an area that includes one or more objects. The one or more objects may be identified from image information obtained from the user device. Positional information for each of the one or more objects may be determined from depth information obtained from a depth sensor installed upon the user device. In some embodiments, the one or more objects may be mapped to object models stored in an object model database. The image information displayed on the user device may be augmented so that it depicts the object models associated with the one or more objects instead of the actual objects.

Abstract: The invention relates to a visualization system (10) for visualizing an accuracy of an alignment of a position and shape of an instrument (33), which has been determined by a position and shape determination device (9), with an image of the instrument. The accuracy is determined for different regions of the instrument as defined by the position and shape and of the image, wherein among these regions at least one region is determined, in which the determined accuracy indicates that it is insufficient. A visualization is then generated in which the determined region is indicated on a representation of the position and shape and/or the image. This visualization guides a user's eyes to the region which should not be missed, while deciding whether, for instance, a navigation of the instrument during a subsequent interventional procedure should be based on this alignment, which in turn allows for an improved navigation accuracy.

Abstract: An information processing apparatus (2000) detects one or more candidate regions (22) from a captured image (20) based on an image feature of a target object. Each candidate region (22) is an image region that is estimated to represent the target object. The information processing apparatus (2000) detects a person region (26) from the captured image (20) and detects an estimation position (24) based on the detected person region (26). The person region (26) is a region that is estimated to represent a person. The estimation position (24) is a position in the captured image (20) where the target object is estimated to be present. Then, the information processing apparatus (2000) determines an object region (30), which is an image region representing the target object, based on each candidate region (22) and the estimation position (24).

Abstract: The present application provides a method of corner detection and an image processing system for detecting corners in an image. The preferred implementation is in software using enabling and reusable hardware features in the underlying vector processor architecture. The advantage of this combined software and programmable processor datapath hardware is that the same hardware used for the FAST algorithm can also be readily applied to a variety of other computational tasks, not limited to image processing.

Abstract: An apparatus includes an extract unit configured to extract features of a first image based on an electromagnetic wave in a first frequency band, an acquire unit configured to acquire motion information about the features, a classify unit configured to classify the features into a first group and a second group based on the motion information, and a remove unit configured to remove, from the first image, a signal corresponding to the feature belonging to the first group.

Abstract: Disclosed herein is a method for facilitating streamlining traveling processes for traveling, in accordance with some embodiments. Accordingly, the method comprises steps of receiving a travel itinerary information from a user device, receiving a location information of the user from the user device, analyzing the travel itinerary information and the location information using a machine learning model, retrieving a traveling requirement, transmitting a document requirement to the user device, receiving a user document from the user device, analyzing the user document, generating a travel application for procuring a travel document for the user, and transmitting the travel application to an agency device associated with an agency. Further, the at least one agency provides the travel document to the user for facilitating the traveling.

Abstract: A scalable tracking system processes video of a space to track the positions of objects within a space. The tracking system determines local coordinates for the objects within frames of the video and then assigns these coordinates to time windows based on when the frames were received. The tracking system then combines or clusters certain local coordinates that have been assigned to the same time window to determine a combined coordinate for an object during that time window.

Abstract: A scalable tracking system processes video of a space to track the positions of people within a space. The tracking system determines local coordinates for the people within frames of the video and then assigns these coordinates to time windows based on when the frames were received. The tracking system then combines or clusters certain local coordinates that have been assigned to the same time window to determine a combined coordinate for a person during that time window.

Abstract: A method of inspecting images on printed products by a computer in a printing machine. Printed products are recorded and digitized by an image sensor of an image inspection system in the course of the image inspection process, and the computer compares them to a digital reference image. If deviations are found, the defective printed products are removed. The computer analyzes the deviations found in the course of the image inspection process together with further data from other system parts and from the machine, determines specific defect classes and the causes thereof based on the defects by machine learning processes, assigns the defects found in the image inspection process to the defect classes in a corresponding way, and displays the classified detected defects with their defect classes and causes to an operator of the machine so that the operator can initiate specific measures to eliminate the defect causes.