Abstract: Methods and systems for computed tomography provide advances in efficiency. The methods operating within the parallel-beam geometry, rather than a divergent beam geometry, for the majority of the operations. In back projection methods perform digital image coordinate transformations on selected intermediate-images, the parameters of one or more coordinate transformations being chosen such that Fourier spectral support of the intermediate-image is modified so that a region of interest has an increased extent along one or more coordinate direction and the aggregates of the intermediate-images can be represented with a desired accuracy by sparse samples.

Abstract: An unmarked body motion tracking system based on multi-Kinect V2 is provided and includes: Kinect V2s, configured to acquire depth data and joint data; analysis modules, configured to analyze data collection characteristics of single Kinect V2 and transmission device assembly requirements; clients, configured to receive and process data collected by Kinect V2s. A process of the data processing includes: based on the data collection characteristics of the single Kinect V2, a client-server model is built to track a human body from different directions; output modules, configured to output layout modes and tracking results of the Kinect V2s. According to the data collection characteristics of the single Kinect V2 and the transmission device assembly requirements, the disclosure minimizes the mutual interference between the opposite Kinect V2s, tracks the human body from different directions, and ensures that the joints in the self-occlusion state are stably tracked by sensors at other angles.

Abstract: Systems and methods for object detection. Object detection may be used to control autonomous vehicle(s). For example, the methods comprise: obtaining, by a computing device, a LiDAR dataset generated by a LiDAR system of autonomous vehicle; and using, by the computing device, the LiDAR dataset and image(s) to detect an object that is in proximity to the autonomous vehicle. The object is detected by performing the following operations: computing a distribution of object detections that each point of the LiDAR dataset is likely to be in; creating a plurality of segments of LiDAR data points using the distribution of object detections; merging the plurality of segments of LiDAR data points to generate merged segments; and detecting the object in a point cloud defined by the LiDAR dataset based on the merged segments. The object detection may be used by the computing device to facilitate at least one autonomous driving operation.

Abstract: In implementations of the subject matter described herein, a solution for object detection is proposed. First, a feature(s) is extracted from an image and used to identify a candidate object region in the image. Then another feature(s) is extracted from the identified candidate object region. Based on the features extracted in these two stages, a target object region in the image and a confidence for the target object region are determined. In this way, the features that characterize the image from the whole scale and a local scale are both taken into consideration in object recognition, thereby improving accuracy of the object detection.

Abstract: Aspects of the present disclosure include methods, systems, and non-transitory computer readable media that perform the steps of receiving a first plurality of snapshots, generating a first plurality of descriptors each associated with the first plurality of snapshots, grouping the first plurality of snapshots into at least one cluster based on the plurality of descriptors, selecting a representative snapshot for each of the at least one cluster, generating at least one second descriptor for the representative snapshot for each of the at least one cluster, wherein the at least one second descriptor is more complex than the first plurality of descriptors, and identifying a target by applying the at least second descriptor to a second plurality of snapshots.

Abstract: A method for tracking movement of a presenter during a videoconference comprises tracking the location of subject of interest; quickly detecting error conditions—such as can occur when a subject of interest moves too quickly or when a subject of interest walks past another person—and quickly reinitiating the tracking sequence to help ensure a positive videoconferencing experience.

Abstract: Noise reduction in images is provided by performing a noise reduction step on blocks of pixels within a video-processing pipeline. The noise reduction step consists of applying a discrete cosine transform (DCT) to the block of pixels, quantizing the resulting DCT coefficients, and performing an inverse of the DCT to the quantized coefficients. The output of that noise reduction step is a block of image pixels similar to the input pixels, but with significantly less image noise. Because the noise reduction step can be performed quickly on small blocks of pixels, the noise reduction can be performed in real-time in a video processing pipeline.

Abstract: Embodiments of the present disclosure disclose an anomaly detector for detecting an anomaly in a sequence of poses of a human performing an activity. The anomaly detector includes an input interface configured to accept input data indicative of a distribution of the sequence of poses, a memory configured to store a discriminative one-class classifier having a pair of complementary classifiers bounding normal distribution of pose sequences in a reproducing kernel Hilbert space (RKHS), a processor configured to embed the input data into an element of the RKHS and classify the embedded data using the discriminative one-class classifier, and an output interface configured to render a classification result.

Abstract: An image analysis device includes a person detecting unit for detecting person images from image information from a surveillance camera, and acquiring both pieces of person image information as a result of the detection of person images, and pieces of attribution information about persons corresponding to the pieces of person image information, and a person narrowing down unit for performing narrowing-down of person image information with respect to the pieces of person image information and the pieces of person attribution information which are acquired by the person detecting unit, on the basis of a person narrowing down rule, to acquire person image information after the narrowing-down and attribution information about a person corresponding to the person image information.

Abstract: An information processing apparatus constructs a virtual space to express a subject by acquiring an image obtained by observing a reality space in which one or more subjects are present, and arranging a plurality of unit volume elements at positions that are determined depending on a subject captured in the acquired image, and the information processing apparatus constructs a virtual space by arranging multiple types of unit volume elements with different sizes.

Abstract: An obstacle recognition device of a vehicle provided with a camera capturing an image around the vehicle, includes an acquiring unit sequentially acquiring the image captured by the camera; a feature point extracting unit extracting a plurality of feature points of an object included in the image; a calculation unit calculating each motion distance of the plurality of feature points between the image previously acquired and the image currently acquired by the acquiring unit; a first determination unit determining whether each motion distance of the feature points is larger than or equal to a first threshold; a second determination unit determining whether each motion distance of the feature points is larger than or equal to a second threshold; and an obstacle recognition unit recognizing an obstacle.

Abstract: A system for identification of bacterial cells in free solution in a sample. A sample handler is adapted to position the sample. A light source illuminates a large volume of the sample. An imager is located to receive light scattered from the sample. A computer it is coupled to receive data transmitted from the imager. A controller is coupled to send control signals to the sample handler and the computer. The imager processes the scattered light to form images of the bacteria and transmits bacteria image information to the computer, wherein the bacteria image information includes intensity values and position data for the bacteria images from which the computer determines the presence of bacteria.

Abstract: An information processing apparatus includes a processor configured to execute first acquisition processing for acquiring a first recognition result and a first recognition probability on target data from a first recognizer, execute second acquisition processing for acquiring a second recognition probability for the first recognition result on the target data from a second recognizer, and execute control for determining which of first processing and second processing with a necessary human workload greater than in the first processing is to be executed for the first recognition result based on the first recognition probability and the second recognition probability.

Abstract: A method for enhancing a set of object scan images may be provided. The set of object scan images comprises at least two scan images. The method comprises determining first distance and determining an interpolated scan image, by applying an interpolation algorithm comprising determining any pixel of the interpolated scan image as a white pixel if the corresponding pixels on the scan images are both white. The same applies to black pixels. The method may further comprise determining any pixel which corresponding pixels are black on one of the two image scans and white on the other image scans as white (black) if a predefined percentage of the directly surrounding pixels is white (black) in the interpolated scan image. Furthermore, the method comprises inserting the interpolated scan image between the first scan image and the second scan image and repeating the above steps until a stop condition is met.

Abstract: A light, such as an ultraviolet (UV) light, is used with a scanning test device in a scanning process of one or more of a user's hands to assess hand cleanliness according to a medical pre-treatment protocol for a medical treatment device, such as for a dialysis treatment using a home dialysis machine. If the scanning process results in a determination that the hands do not pass a cleanliness standard, the user is requested to perform a cleaning protocol and re-perform a scanning test. The scanning test device may be a smartphone, tablet device and/or other smart device running a software app that obtains and scans an image of the user's hand(s) illuminated by the UV light and makes an assessment of hand cleanliness according to an assessment algorithm. After passing the scanning test, the scanning test device signals to the treatment machine that the medical pre-treatment protocol may continue.

Abstract: A method and an apparatus for recognizing a descriptive attribute of an appearance feature include obtaining a location feature of an appearance feature of a target image to determine a location of a part of an object in a preset object model indicated by the appearance feature, where the location feature of the appearance feature indicates the location of the part of the object in the preset object model indicated by the appearance feature, recognizing a target region based on the location feature, where the target region includes the part of the object, performing feature analysis on the target region, recognizing a descriptive attribute of the appearance feature of the object, and determining the location feature of the appearance feature having a local attribute.

Abstract: Provided are a method and an apparatus wherein an object is distinguished from the background of the object by using a sensor unit including at least one sensor, the distances to measurement points of the background and/or the object are measured, and information on the shape of at least one part constituting the object is acquired on the basis of the measured distances.

Abstract: An operating assistance method for a working device or for a vehicle. Object boxes for an object in a field of view of the working device are obtained at consecutive times. From object boxes of a given object, for images recorded in succession or direct succession, an instantaneous change of scale of an object box for the specific object, and an instantaneous lateral change of position of the object box for the specific object, are determined. An object box predicted in the future is determined from the current change of scale, and from the instantaneous lateral change in position for an object box for a specific object. The position of the predicted object box and/or the ratio of a lateral extension of the predicted object box to a lateral extension of a covered field of view and/or of the recorded images are determined and evaluated.

Abstract: A method, system and computer readable storage media for segmenting individual intra-oral measurements and registering said individual intraoral measurements to eliminate or reduce registration errors. An operator may use a dental camera to scan teeth and a trained deep neural network may automatically detect portions of the input images that can cause registration errors and reduce or eliminate the effect of these sources of registration errors.

Abstract: A system, including a processor and a memory, the memory including instructions to be executed by the processor to identify first object features from sensor data acquired by a stationary sensor at a first time step, determine second object features at a second time step. The instructions can include further instructions to determine one or more object clusters of first object features by determining distances measured in pixels between the first object features and corresponding second object features and comparing the distances to one or more mean distances and determine one or more object groups of inlier first object features in the one or more object clusters by determining a plurality of similarity transformations for a plurality of random samples of first object features and determining inlier first object features based on maximizing the number of first object features included in a similarity transformation.