Abstract: Visibility of a license plate and color reproducibility of a vehicle body are improved in a monitoring camera. A vehicle body area detection unit detects a vehicle body area of a vehicle from an image signal. A license plate area detection unit detects a license plate area of the vehicle from the image signal. A vehicle body area image processing unit performs processing of the image signal corresponding to the detected vehicle body area. A license plate area image processing unit performs processing different from the processing of the image signal corresponding to the vehicle body area on the image signal corresponding to the detected license plate area. A synthesis unit synthesizes the processed image signal corresponding to the vehicle body area and the processed image signal corresponding to the license plate area.

Abstract: Configurations are disclosed for presenting virtual reality and augmented reality experiences to users. The system may comprise an image capturing device to capture one or more images, the one or more images corresponding to a field of the view of a user of a head-mounted augmented reality device, and a processor communicatively coupled to the image capturing device to extract a set of map points from the set of images, to identify a set of sparse points and a set of dense points from the extracted set of map points, and to perform a normalization on the set of map points.

Abstract: According to an aspect of an exemplary embodiment, an apparatus for avoiding region of interest (ROI) re-detection includes a detector configured to detect an ROI from an input medical image; a re-detection determiner configured to determine whether the detected ROI corresponds to a previously-detected ROI using pre-stored user determination information; and an ROI processor configured to perform a process for the detected ROI based on the determination.

Abstract: Embodiments can provide a computer-implemented method for simultaneous multi-slice pulse wave velocity measurement, the method comprising simultaneously acquiring a plurality of multiple parallel images slices from a medical imaging device; shifting the plurality of image slices through modulation of the line-by-line phase patterns for each slice in the plurality of slices; deriving a plurality of image waveforms from the plurality of slices; measuring a distance between a plurality of imaging planes corresponding to the plurality of image slices; determining, for each of the image waveforms, a time-to marker; determining the temporal shift by calculating the difference between the time-to markers; and computing the pulse wave velocity by dividing the distance between the plurality of imaging planes by the temporal shift.

Abstract: An example device in accordance with an aspect of the present disclosure includes an identification engine, a clustering engine, and a weighting engine. The identification engine is to identify User Interface (UI) elements of an application under test based on an image processing analysis of screens of the application under test. The clustering engine is to cluster the UI elements into at least one cluster based on at least one feature of the UI elements. The weighting engine is to assign score weights to the UI elements of a given screen according to which of the at least one cluster that a given one of the UI elements is clustered in.

Abstract: There is provided an information processing apparatus that self position estimation with high robustness is possible, the information processing apparatus including: a tracking unit, a region estimation unit, and an estimation processing unit. The tracking unit that acquires an image captured by an image capture unit disposed at a moving object, and corresponds characteristic points included in the image captured before movement and the image captured after the movement, the moving object moving accompanying a rotation motion. The region estimation unit that acquires information about the movement, and estimates regions where two-dimensional positions of the characteristic points are less changed viewed from the moving object before and after the movement of the moving object on the basis of the information. The estimation processing unit that performs self position estimation of the moving object using the characteristic points within the regions corresponded by the tracking unit.

Abstract: A driver monitoring device is provided. The driver monitoring device includes a detection unit that detects an unbalanced posture of a driver based on an image of a driver's seat of a vehicle captured by a camera; a determination unit that determines whether or not the unbalanced posture of the driver detected by the detection unit is a habitual posture of the driver; and a notification unit that notifies the driver of the unbalanced posture in different manners in accordance with whether the unbalanced posture determined is the habitual posture of the driver or the unbalanced posture determined is other than the habitual posture of the driver.

Abstract: A method includes receiving a plurality of video frames from a video source, wherein each video frame of the plurality of video frames comprises a view of a geolocation. The method further includes detecting a first object entering a first side of a first video frame of the plurality of video frames. The method further includes determining, from the plurality of video frames, that the first object has stopped in an area of the geolocation for at least a threshold amount of time. The method further includes detecting the first object leaving a second side of a second video frame of the plurality of video frames. The method further includes identifying, by a computer processing device, the area of the geolocation as a region of interest based on the detecting the first object leaving.

Abstract: Method for providing position-based information to a mobile device with at least one imaging device includes obtaining, using the imaging device, an image including a stationary pattern of pixels, searching through a database of pixel patterns for a pixel pattern that most closely matches the pattern of pixels in the obtained at least one image, the database containing pixel patterns and positional information about the pixel patterns, and retrieving from the database as a result of the searching, positional information about one of the pixel patterns that is deemed to most closely match the pattern of pixels in the obtained at least one image. Data is provided to the mobile device, i.e., to a data output device or functionality thereof, dependent on the retrieved positional information about one of the pixel patterns that is deemed to most closely match the pattern of pixels in the obtained at least one image.

Abstract: A medical signal processing device receives an image signal in accordance with a result of examining inside of a subject and processes the image signal that includes a plurality of pixel data groups of respective pixels arrayed at a constant interval among pixels sequentially arrayed in a predetermined direction in an image made of pixels arrayed in a matrix. The pixel data groups are data of respective pixels that are different from each other, and the pixel data groups are input in the medical signal processing device in parallel. The medical signal processing device includes a distribution processing unit configured to generate a plurality of distributed image signals by combining, among the pixel data groups, pixel data groups of respective pixels that are separate from each other, and the distributed image signals are transmitted to an external medical control device through a plurality of respective signal transmission paths.

Abstract: An example system includes a processor to train a convolutional neural network (CNN) to detect features, and train fully connected layers of the CNN to map detected features to semantic descriptors, based on a data set including one or more lesions. The processor is to also receive a medical image to be analyzed for lesions. The processor is to further extract feature maps from the medical image using the trained CNN. The processor is also to detect a region of interest via the trained CNN and generate a bounding box around the detected region of interest. The processor is to reduce a dimension of the region of interest based on the feature maps. The processor is to generate a semantic description of the region of interest via the trained fully connected layers.

Abstract: A medical signal processing device processes an image signal received in accordance with a result of examining inside of a subject. The image signal includes pixel data groups that are data of respective pixels different from each other and received by the medical signal processing device in parallel. The medical signal processing device includes a distribution processing unit configured to generate distributed image signals by distributing the pixel data groups, and the distribution processing unit distributes the pixel data groups such that, among the pixel data groups, pieces of data at bit positions of most significant digits of the pixel data groups of pixels adjacent to each other are included in the respective distributed image signals different from each other. The distributed image signals are transmitted to an external medical control device through respective signal transmission paths.

Abstract: Aspects of the disclosure include a method for indicating a location of a first object by a wearable device. The method includes determining the first object; and, when a preset condition is satisfied, locating the first object and highlighting the first object on a display.

Abstract: Systems and methods for determining athletic attributes are disclosed. Aspects of this disclosure relate to determining athletic attributes of an athlete from image data. One or more determinations may be based alterations of image data between different images, such as alterations in pixels representing objects or portions of objects. Image data may be utilized to determine whether certain thresholds are met. Various threshold levels may be applied to one or more objects represented in the image data. Landmarks/distance calibrations may be utilized from time-stamped image data to allow for precise measuring of performance (including, but not limited to: sprint or agility times, flight time for vertical jump, distance for throws). Data retrieved or derived from the image data may be used in scoring and/or ranking athletes. Such data may be used to provide training advice or regimes to the athletes or other individuals, such as coaches or trainers.

Abstract: Techniques and systems are provided for processing video data. For example, techniques and systems are provided for performing context-aware object or blob tracker updates (e.g., by updating a motion model of a blob tracker). In some cases, to perform a context-aware blob tracker update, a blob tracker is associated with a first blob. The first blob includes pixels of at least a portion of one or more foreground objects in one or more video frames. A split of the first blob and a second blob in a current video frame can be detected, and a motion model of the blob tracker is reset in response to detecting the split of the first blob and the second blob. In some cases, a motion model of a blob tracker associated with a merged blob is updated to include a predicted location of the blob tracker in a next video frame.

Abstract: Systems, devices, and methods are presented for segmenting an image of a video stream with a client device by receiving one or more images depicting an object of interest and determining pixels within the one or more images corresponding to the object of interest. The systems, devices, and methods identify a position of a portion of the object of interest and determine a direction for the portion of the object of interest. Based on the direction of the portion of the object of interest, a histogram threshold is dynamically modified for identifying pixels as corresponding to the portion of the object of interest. The portion of the object of interest is replaced with a graphical interface element aligned with the direction of the portion of the object of interest.

Abstract: A data-enhanced video viewing system scans videos in order to detect and extract certain objects, such as human faces, so as to compile non-time based synopses, including “facelines” of people appearing in the video sequence. It can also provide a time-based synopsis that includes timestamps for all detected objects. The data-enhanced video viewing system can be deployed on a network for a client to request data extraction on one or more designated videos. The designated video may be one of those that have been uploaded to social networks, uploaded to online video hosting sites, streamed over the Internet or other network, or uploaded directly by the user.

Abstract: In tomosynthesis imaging for obtaining a tomographic image from a plurality of projected images, in a case where a reconstruction condition and the tone conversion condition have been changed, control is performed to determine whether or not to use the changed tone conversion condition for tone conversion processing to be performed on a tomosynthesis image reconstructed in accordance with the changed reconstruction condition.

Abstract: A method and system analyzes multi-resolution medical images. The method includes receiving one or more multi-resolution medical images of one or more tissues. Each multi-resolution medical image is divided into a plurality of segments. Thereafter, each segment of the plurality of segments of each multi-resolution medical image is processed in parallel, utilizing one or more computation nodes, wherein each computation node includes one or more Graphical Processing Units (GPUs). The results corresponding to each segment of a multi-resolution medical image are collated, and a collated report is displayed.

Abstract: An object is to more accurately compare diagnosis indexes with each other, which are calculated from data obtained in different environments with a cardiac-function diagnostic medicine. A conversion function calculation unit acquires a first phantom Heart/Mediastinum ratio (H/M ratio) and a second phantom H/M ratio based on a phantom, the first phantom H/M ratio that is an H/M ratio of the phantom in the first imaging environment being acquired by performing, based on phantom data that is data of a first phantom image obtained by imaging the phantom in the first imaging environment and digital phantom data that is data of a digital phantom including a cardiac ROI and a mediastinum ROI, positioning of the digital phantom on the first phantom image, and by calculating based on the phantom data of the first phantom image to which the cardiac ROI and the mediastinum ROI are set; and obtains a conversion function based on the first phantom H/M ratio and the second phantom H/M ratio.