Systems and methods are presented for generating statistics associated with a performance of a participant in an event, wherein pose data associated with the participant, performing in the event, are processed in real time. Pose data associated with the participant may comprise positional data of a skeletal representation of the participant. Actions performed by the participant may be determined based on a comparison of segments of the participant's pose data to motion patterns associated with actions of interests.

A method for using an assembled three-dimensional image to construct a three-dimensional model for determining a path through a lumen network to a target. The three-dimensional model is automatically registered to an actual location of a probe by tracking and recording the positions of the probe and continually adjusting the registration between the model and a display of the probe position. The registration algorithm becomes dynamic (elastic) as the probe approaches smaller lumens in the periphery of the network where movement has a bigger impact on the registration between the model and the probe display.

The present disclosure relates to an information processing apparatus, an information processing method, and a program capable of providing more effective learning content in learning motion of a body.

An adjustment unit generates an adjusted second virtual object by adjusting, on the basis of feature point information of a first person included in a first virtual object reflecting a body motion of the first person, a second virtual object reflecting a body motion of a second person to be superimposed on the first virtual object. The technology according to the present disclosure can be applied to, for example, an information processing apparatus such as a smartphone.

A method for skeletonizing the strands of a composite material part in a 3D image having a step of detecting oriented section centers of the strands and a link from each center to the closest center having the same orientation, the detection being carried out by means of at least one reference volume having an oriented centered strand pattern, the detection step having, for each reference volume: • a step of determining portions of the image, • a step of calculating a correlation score between the reference volume and each portion associated with the central voxel of each portion, so as to obtain a correlation score for each voxel of the image; and • a step of determining the strand centers corresponding to the voxels having a correlation score which corresponds to a local maximum.

Disclosed herein is a robotic system comprising a robotic arm, an end effector coupled to a distal end of a robotic arm, one or more cameras, and a processors configured to construct a three-dimensional (3D) model of a user based on received data from the one or more cameras, identify automatically a target therapy point on the user based on the constructed 3D model, and actuate the end effector to apply a therapy to the target therapy point.

The present invention provides a method of angiography for cerebrovascular obliteration includes: using a classifier to obtain a 2D medical image using from a plurality of Multiphase CTA images; using a gray-scale conversion to obtain a N*M pixels grayscale image; filtering the grayscale image not being meet a condition of grayscale threshold and performing an image binarization to obtain a binarized image; confirming at least one vascular region and performing an image skeletonization; filtering according to a vascular image features of a vascular region to obtain a vascular-enhanced image; using a fracture analysis to obtain an analysis report related to a plurality of quantifying parameters of vascular characteristics; wherein the quantifying parameters of vascular characteristics comprises a quantitative value of fractal dimension (FD), vessel density (VD), skeleton density (SD) and vascular diameter index (VDI). Therefore, improve the accuracy of clinician diagnosis and the survival rates of patients with ischemic stroke

A height measurement method includes obtaining an image including a target object and a pose of a camera used when the image is photographed, obtaining pixel coordinates of at least two key skeleton points of the target object in the image, obtaining three-dimensional coordinates of the key skeleton points based on the pose of the camera and the pixel coordinates of the key skeleton points, and determining height data of the target object based on the three-dimensional coordinates of the at least two key skeleton points.

A system for detection and identification of objects and obstacles near, between or on railway comprise several forward-looking imagers adapted to cover each different range forward and preferably to be sensitive each to different wavelength of radiation, including visible light, LWIR, and SWIR. The substantially homogeneous temperature along the rail the image of which is included in an imager frame assists in identifying and distinguishing the rail from the background. Image processing is applied to define living creature in the image frame and to distinguish from a man-made object based on temperature of the body. Electro optic sensors (e.g. thermal infrared imaging sensor and visible band imaging sensor) are used to survey and monitor railway scenes in real time.

Artwork carrying machine readable data is generated by editing artwork according to a data signal or transforming the data signal into artwork. The machine-readable data signal is generated from a digital payload and converted into an image tile. Artwork is edited according to the image tile by moving graphic elements, adapting intersections of lines, or altering line density, among other techniques. Artwork is generated from the data signal by skeletonizing it and applying morphological operators to a skeletal representation, such as a medial axis transform. Artistic effects are introduced by filtering the data signal with directional blurring or shape filters.

An image processing apparatus includes a first skeleton extraction means, a second skeleton extraction means, and an integration unit. The first skeleton extraction means discriminates a valid region and an invalid region in a fingerprint image which is input, and extracts skeleton lines in the valid region. The second skeleton extraction means extracts skeleton lines in the invalid region. The integration unit generates a skeleton image by integrating the skeleton lines extracted in the valid region and the skeleton lines extracted in the invalid region.