Abstract: A medical information processing apparatus according to an embodiment includes processing circuitry. The processing circuitry obtains image data rendering a blood vessel of a patient. The processing circuitry performs a fluid analysis on the obtained image data and calculates an index value related to a blood flow in the blood vessel with respect to each of a plurality of positions in the blood vessel. With respect to the index values to be calculated, the processing circuitry selects a position in which a first value is to be obtained from among the plurality of positions or selects a value serving as the first value from among the index values exhibited in positions. The processing circuitry causes a display to display the first value in a predetermined display region thereof used for displaying the first value.

Abstract: A method for identifying a pore color of at least one skin pore. The method includes obtaining at least one image of a subject, extracting a pore image from the obtained image, in which the extracted pore image identifies a boundary of the at least one skin pore, and superimposing the obtained image and the extracted pore image to identify the pore color within the identified boundary of the at least one skin pore.

Abstract: Example image processing methods and apparatuses are disclosed. One example image processing method includes obtaining a video stream, where the video stream includes a first frame of image, a second frame of image, and a third frame of image that are adjacent in time sequence. The video stream can then be decoded to obtain a first alignment frame, a second alignment frame, and at least one residual between the first frame of image, the second frame of image, and the third frame of image. At least one residual frame can then be generated based on the at least one residual. Super resolution processing can then be performed on the second frame of image based on the at least one residual frame, the first alignment frame, and the second alignment frame to obtain an additional second frame of image obtained after super resolution.

Abstract: A computing system may perform image processing on image data acquired by a camera at a property to determine at least a first feature of the image data. Based at least in part on a determination that the first feature satisfies a rule, the computing system may generate a vector representing a plurality of characteristics of a face represented in the image data. The vector may then be used to determine a particular person is represented in the image data.

Abstract: A system for inspecting a stator stack includes a rotary table, an imaging device configured to take a plurality of images of a portion of the stator stack including a stator slot, an illuminator configured to apply illumination through the stator slot, and an alignment and monitoring system configured to monitor and orient the stator slot relative to the imaging axis. The alignment and monitoring system includes a tilting system configured to move the stator slot between a plurality of orientations relative to an imaging axis, the imaging device configured to take a respective image at each of the plurality of orientations, a controller configured to control the tilting system based on one or more measurements of each image, and a processor configured to analyze each image and select an orientation of the stator slot as an optimal orientation for inspection of the stator slot.

Abstract: A multi-object tracking method based on authenticity hierarchizing and occlusion recovery relates to the technical field of multi-object tracking for security management and control of complex scenes. The method includes the following steps: image acquisition, object detection, authenticity hierarchizing, hierarchical association and outputting tracks. The multi-object tracking method is helpful to solve the long-term puzzling occlusion problem in the field of multi-object tracking, the constructed new algorithm framework can achieve an advanced tracking performance, improve the adaptability of the method to complex environments, and adapt to more difficult video surveillance security control tasks.

Abstract: System and methods for tracking transaction flow through a customer service area. The present invention provides automated, non-intrusive tracking of individuals, based on a series of still image frames obtained from one or more colour sensors. Images of individuals are extracted from each frame and the datasets resulting from the cropped images are compared across multiple frames. The datasets are grouped together into groups called “tracklets”, which can be further merged into “customer sets”. Various pieces of metadata related to individuals' movement (such as customer location and the duration of each transaction state) can be derived from the customer sets. Additionally, individual images may be anonymized into mathematical representations.

Abstract: Real time location systems are provided including one or more ultra-wideband (UWB) sensors positioned in an environment; one or more image capture sensors positioned in the environment; and at least one UWB tag associated with an object in the environment to provide a tagged item in the environment. The one or more UWB sensors and the one or more image capture sensors are integrated into at least one location device. The at one location device includes a UWB location device, a combination UWB/camera location device and/or a camera location device. A location of the tagged item is tracked using the at least one location device. and wherein a location of the tagged item is tracked using the at least one location device.

Abstract: A system comprises a memory that stores computer executable components; and a processor that executes the computer executable components stored in the memory. A communication component receives a stream of medical images from a medical image data source via a network for displaying in one or more viewports of a medical image visualization application that provides interactive functionalities in association with the displaying. A buffer component stores the medical images, in one or more buffers, as the respective medical images are received. A monitoring component monitors user activity with respect to a rendered subset of the medical images in the one or more viewports in association with usage of the interactive functionalities. A buffer management component regulates storing of the medical images in the one or more buffers by the buffer component as a function of the user activity to facilitate seamless rendering of the medical images.

Abstract: A method, system and computer program product, the method comprising: obtaining a first multiplicity of images from an overhead capture device overlooking a body of water; detecting a swimmer in some of the images, wherein the swimmer is outside the body of water or separated from other swimmers; determining two descriptors of the person, based on the images, the first descriptor related to a portion of the swimmer outside the water, the second related to a portion inside the water, the descriptors determined upon visual characteristics extracted from the images; obtaining a second multiplicity of images from the device; and tracking the swimmer in the second multiplicity of images, said tracking comprises detecting the swimmer using either descriptor, said detecting the swimmer is performed with respect to an image from the second multiplicity of images in which the swimmer is partially occluded by other swimmers or adjacent to other swimmers.

Abstract: Disclosed herein are systems and method for detecting small objects in an image using a neural network (NN). An exemplary method may include: receiving a first NN that is trained on a dataset including a plurality of images depicting various objects; identifying a first structure of the first NN, the first structure indicative of each layer and layer size in the first NN; determining, based on the first structure, whether the first NN can classify an object less than a threshold size in an input image; in response to determining that the first NN cannot classify the object, identifying a subset of detection layers in the first NN; generating and training a second NN that has a second structure in which the subset of detection layers are replaced by at least one layer not in the subset; and receiving, from the second NN, a classification of the object.

Abstract: A computer-implemented method comprises: providing at least two exploratory views; segmenting a first object in the at least two exploratory views to determine first two-dimensional object masks; segmenting the second object in the at least two exploratory views tow determine second two-dimensional object masks; determining a first three-dimensional object mask as a function of the first two-dimensional object masks; determining a second three-dimensional object mask as a function of the second two-dimensional object masks; and determining an overlap of the first object and the second object for at least one capture trajectory as a function of the first three-dimensional object mask and the second three-dimensional object mask.

Abstract: A method of aligning two 3D digital representations of at least a part of each of the upper and lower jaw of a patient, the method including segmenting the 3D digital representations to determine the shape and position of each of the patient's teeth in each of the 3D digital representations; and using a set of known anatomical concepts to constrain the fit of the two 3D digital representations to get a preliminary fit.

Abstract: An object tracking system that includes a sensor that is configured to capture frames of at least a portion of a global plane for a space. The system is configured to receive a first frame from the sensor. The first frame includes a region-of-interest (ROI) marker within the space. The system is further configured to identify pixel locations within the first frame corresponding with the ROI marker and to define a zone for subsequent frames from the sensor corresponding with the pixel locations. The system is further configured to receive a second frame from the sensor, to detect an object within the zone, and to identify the object. The system is further configured to determine a person is within the second frame and to modify a digital cart that is associated with the person based on the identified object.

Abstract: A shading correcting method for a real-time image is disclosed and includes following steps: obtaining a real-time image through an image sensor; reading a stored previous image which is time-adjacent to the real-time image; computing an image reference data of the previous image; computing an adjusting parameter in accordance with the image referring data and an equipment reference data of the image sensor; adjusting a gain table based on the adjusting parameter to generate an adjusted gain table, wherein the gain table records multiple compensation values each for compensating each corresponding pixel of the real-time image; correcting the real-time image in accordance with the adjusted gain table to generate an adjusted image; and, outputting the adjusted image.

Abstract: Systems and methods for measuring service times at a retail establishment. One or more video cameras are coupled to data processors. The video frames from the video cameras are analyzed to detect a customer at the service counter and, at the detection of a specific event, a timer is started. The customer detected at the service counter is then tracked through various video frames until the customer has left or is about to leave. The timer is then stopped and the elapsed time is stored. The retail establishment may be a quick service restaurant and various video and image processing methods may be used to detect, track, and recognize the customer.

Abstract: Data is received that includes a feed of images of a plurality of objects passing in front of an inspection camera module forming part of a quality assurance inspection system. Thereafter, a machine learning model is used to generate a representation of each image. These representations are analyzed to determine a type of object captured in the corresponding image. This analysis can be provided to a consuming application or process for quality assurance analysis.

Abstract: Systems, methods, and devices described in the present disclosure provide technology for detecting features of interest depicted in a video stream supplied by a camera-equipped drone and adjusting the flight pattern of the drone to increase the amount of time in which the features of interest are within the line of sight of the drone. In addition, the present disclosure provides technology for detecting when events of interest occur at the features of interest and alerting personnel when the events occur. In some examples, the technology of the present disclosure also determines a format for an alert (e.g., a push notification) based on an event type so that personnel who receive the alert are apprised of the urgency of the event based on the format.

Abstract: Insects can be classified into a category (e.g., sex category, species category, size category, etc.) using a variety of different classification approaches including, for example, an industrial vision classifier and/or a machine learning classifier. At least some classification approaches may be used in real-time to make real-time decisions and others can be used to validate earlier-made real-time decisions.

Abstract: An embodiment of a semiconductor package apparatus may include technology to analyze an electronic image to determine indirect information including one or more of shadow information and reflection information, and provide the indirect information to a vehicle guidance system. Other embodiments are disclosed and claimed.