Abstract: A device, method, and non-transitory computer readable medium for interactive 3D visualization of ultrasound images of a supraspinatus tendon injury. Ultrasound images are acquired of a region in which the supraspinatus tendon injury is suspected. The ultrasound images are preprocessed, and energy of the preprocessed ultrasound images is minimized. A set of supraspinatus tendon images are extracted from low energy preprocessed ultrasound images. A morphological operation is performed on the set of supraspinatus tendon images to generate a smoothed set of supraspinatus tendon images. A binary mask is applied to the smoothed set of supraspinatus tendon images to detect boundary points of the supraspinatus tendon and generate a set of segmented image frames. The set of segmented image frames are arranged based on spatial position of each segmented image frame with respect to the supraspinatus tendon. A 3D representation of the supraspinatus tendon is reconstructed and rendered on a display.

Abstract: Aspects of the present disclosure include methods for generating a sampled profile including a plurality of sampling points having a plurality of characteristic values associated with the detected non-visible light, identifying one or more macroblocks each includes a subset of the plurality of sampling points, calculating a number of occurrences of the local pattern value within each subset of the plurality of the sampling points for each of the one or more macroblocks, generating a first array including a plurality of weighted values by calculating the plurality of weighted values based on the numbers of occurrences of the local pattern value and corresponding sizes of the one or more macroblocks, assigning a unique index to each of the plurality of weighted values, generating a second array of the unique index by ranking the plurality of weighted values, and generating a third array including a plurality of ranking distances.

Abstract: Methods and systems for performing image analytics using graphical reporting associated with clinical images. One system includes at least one data source and a server. The server includes an electronic processor and an interface for communicating with the data source. The electronic processor is configured to receive training information from the at least one data source over the interface. The training information includes a plurality of images and graphical reporting associated with each of the plurality of images. Each graphical reporting includes a graphical marker designating a portion of one of the plurality of images and diagnostic information associated with the portion of the one of the plurality of images. The electronic processor is also configured to perform machine learning to develop a model using the training information. The model is used to automatically analyze an image.

Abstract: A method, apparatus and device for correcting a vascular pressure difference are disclosed. An intracavity imaging technology is used to acquire images in a main branch blood vessel. A plurality of blood vessel cross sections are obtained using the images, and an area of a cutting plane of a side branch blood vessel is directly calculated by using the blood vessel cross sections. The blood vessel difference is then corrected by using the cutting area.

Abstract: A computing device of a first vehicle may receive a first image and a second image of a second vehicle having flashing light signals. The computing device may determine, in the first image and the second image, an image region that bounds the second vehicle such that the image region substantially encompasses the second vehicle. The computing device may determine a polar grid that partitions the image region in the first image and the second image into polar bins, and identify portions of image data exhibiting a change in color and a change in brightness between the first image and the second image. The computing device may determine a type of the flashing light signals and a type of the second vehicle; and accordingly provide instructions to control the first vehicle.

Abstract: Aspects of the present disclosure include methods for generating a sampled profile including a plurality of sampling points having a plurality of characteristic values associated with the detected non-visible light, identifying one or more macroblocks each includes a subset of the plurality of sampling points, calculating a number of occurrences of the local pattern value within each subset of the plurality of the sampling points for each of the one or more macroblocks, generating a first array including a plurality of weighted values by calculating the plurality of weighted values based on the numbers of occurrences of the local pattern value and corresponding sizes of the one or more macroblocks, assigning a unique index to each of the plurality of weighted values, generating a second array of the unique index by ranking the plurality of weighted values, and generating a third array including a plurality of ranking distances.

Abstract: Computer aided inspection systems (CAIS) and method for inspection, error analysis and comparison of structures are presented herein. In some embodiments, a CAIS may include a SLAM system configured to determine real-world global localization information of a user in relation to a structure being inspected using information obtained from a first sensor package, a model alignment system configured to: use the determined global localization information to index into a corresponding location in a 3D computer model of the structure being inspected; and align observations and/or information obtained from the first sensor package to the local area of the model 3D computer model of the structure extracted; a second sensor package configured to obtain fine level measurements of the structure; and a model recognition system configured to compare the fine level measurements and information obtained about the structure from the second sensor package to the 3D computer model.

Abstract: An apparatus includes an input interface and a processor. The input interface may be configured to (i) receive a sequence of video frames of a targeted view of an environment and (ii) collect data samples from a gravity sensor (G-sensor) and a gyroscopic sensor. The processor may be configured to (i) detect axes transitions using the data samples from the gyroscopic sensor, (ii) perform, in real-time, electronic image stabilization, (iii) generate a computed horizon level based on the data samples from the G-sensor and the data samples from the gyroscopic sensor, (iv) perform, in real-time, a rotational offset compensation on stabilized captured image data of the sequence of video frames to maintain alignment of a respective horizon in each frame of the sequence of video frames with the computed horizon level, and (v) generate video analytics for the sequence of video frames using the compensated and stabilized captured image data.

Abstract: The present disclosure relates to the technical field of terminals, and particularly relates to a method and device for terminal-based object recognition, and an electronic device. The method includes: receiving a function instruction for simulated magnifier input to a terminal by a user; activating a camera of the terminal according to the function instruction for simulated magnifier; determining an object to be recognized based on an object photographed by the camera; acquiring a physical distance between the object to be recognized and the camera, and acquiring a preset focal length corresponding to the physical distance; generating, according to the preset focal length, a first image corresponding to the object to be recognized, and displaying the first image; performing image processing and image recognition on the first image; and displaying information of the object to be recognized at the terminal according to a result of image processing and image recognition.

Abstract: The present disclosure relates to a positioning system suitable for use in an imaging system. The positioning system may include one or more cameras configured to capture images or videos of an imaging object and surrounding environment thereof for ROI targeting or patient position recognition. The positioning system may also include one or more position probes and sources configured to determine an instant location of an imaging object or an ROI thereof in a non-contact manner.

Abstract: A person count apparatus obtains a person count result of a region person count that counts the number of persons existing in a predetermined region of an image captured by an image capturing unit and a person count result of a passing person count that counts the number of persons passing a predetermined line set in an image captured by the image capturing unit, displays a still image captured by the image capturing unit in a time period corresponding a person count result selected from the plurality of person count results for each time period based on the region person count, and reproduce a moving image captured by the image capturing unit on the display unit in a time period corresponding to a person count result selected from the plurality of person count results for each time period based on the passing person count.

Abstract: An unmanned aerial vehicle (UAV) includes a propulsion system, a camera system, a processor, and communications circuitry. The camera system includes an image channel with a band pass filter centered near a spectral line of a material associated with wildfires, and the camera system captures a spectral line emission image within a region of a potential wildfire. The processor uses the captured spectral line emission image to identify an emission event indicative of a wildfire. The communications circuitry transmits, to a dispatch system, data describing a location of an identified emission event. The dispatch system may dispatch firefighting resources to the location of the wildfire.

Abstract: The present disclosure provides a microbe engineering platform that permits optimization of microbe fitness levels to optimize a microbe's suitability for industrial fermentation. The disclosed platform identifies an association between microbe properties and microbe fitness levels. The association between microbe properties and microbe fitness levels may be used to identify candidate microbes with desired fitness levels. The identified candidate microbes may be used to further optimize the industrial fermentation process.

Abstract: A user device may capture an image including an object, and may identify the object, including determining an outline of the object. The user device may determine a first center point of the object and an angle of orientation of the object in relation to the image. The user device may rotate the image based on the angle of orientation, including changing one or more dimensions of the image. The user device may, after rotating the image, determine the one or more dimensions of the rotated image, calculate one or more offset values associated with changing the one or more dimensions of the rotated image, and determine a second center point of the object based on the first center point and the one or more offset values. The user device may perform an action related to the rotated image based on determining the second center point of the object.

Abstract: An evaluation device includes a state determination unit which is configured to determine a state of cells which are an observation target under non-standard conditions on the basis of information acquired from an image of cells under standard conditions.

Abstract: According to one embodiment, a system for determining a position of a vehicle includes an image sensor, a top-down view component, a comparison component, and a location component. The image sensor obtains an image of an environment near a vehicle. The top-down view component is configured to generate a top-down view of a ground surface based on the image of the environment. The comparison component is configured to compare the top-down image with a map, the map comprising a top-down light LIDAR intensity map or a vector-based semantic map. The location component is configured to determine a location of the vehicle on the map based on the comparison.

Abstract: A system and method for processing human related data to make personalized and context aware decisions with distributed machine learning at an edge and a cloud is disclosed. A nearest edge computing device receives first, second and third sensed signals from first, second and third sensory devices, determines when the first, second and third sensed signals exceed corresponding thresholds, correlates pairs of the sensed signals to generate multiple correlation patterns, determines a lag time between the first sensed signal exceeding the first threshold and the second sensed signal exceeding the second threshold, provides each of the multiple correlation patterns and the lag time as inputs to multiple long short term memory (LSTM) neural networks, controls the multiple LSTM neural networks to provide outputs, and maps the patient to a stage of a medical condition based at least in part on the multiple correlation patterns and the lag time.

Abstract: Systems and methods for monitoring movements. A method includes detecting motion based on first localization data related to a localization device moving in a distinct motion pattern, wherein the first localization data is based on sensor readings captured by at least one sensor; correlating the detected motion to a known motion of the localization device based on respective times of the first localization data and of the localization device; localizing the localization device with respect to a map based on the correlation; tracking at least one first location of an object based on second localization data captured by the at least one sensor, wherein the at least one first location is on the map, wherein the tracking further comprises identifying at least one second location of the object based on the second localization data and determining the at least one first location based on the at least one second location.

Abstract: A method for generating a UAV flight trajectory. The method includes acquiring map data of a to-be-reconstructed area; the map data includes a satellite map image and a plane map image; acquiring building silhouettes of each building in a to-be-reconstructed area from a plane map image; acquiring height data of each building from a satellite map image; generating an initial model according to the building silhouettes and height data of each building; determining a view set according to an initial model; generating a flight trajectory from a view set. The initial model can be established without pre-flight of the to-be-reconstructed area, and the UAV flight trajectory can be directly generated, so that the calculation amount of data is reduced.

Abstract: A system includes a sensor, a weight sensor, and a tracking subsystem. The tracking subsystem receives an image feed of top-view images generated by the sensor and weight measurements from the weight sensor. The tracking subsystem detects an event associated with an item being removed from a rack in which the weight sensor is installed. The tracking subsystem determines that a first person and a second person may be associated with the event. In response, the tracking subsystem dilates contours associated with the first and second person from a first depth to a second depth until the contours enter a zone adjacent to the rack. A number of iterations is determined for each contour to enter the zone adjacent to the rack. If the first person's contour enters the zone in fewer iterations, the item is assigned to the first person.