This application provides a method of detecting printing defects. The method includes obtaining a first image of each character in a reference image. A third image of each character is obtained based on the first image of each character, a fourth image of each character is obtained based on a second image of each character obtained from an image to be detected. Once a fifth image of each character is obtained based on the third image of each character, a sixth image of each character is obtained according to the fourth image and the fifth image of each character, a detection result of each character in the image to be detected is determined according to the fifth image and the sixth image of the each character.

Disclosed is a system for monitoring an activity performed by the subject. The system comprises a non-imaging sensor configured to detect the subject in a scan area, wherein the subject is detected by reflected waveform thereby. The system also comprises a processing arrangement communicably coupled to the non-imaging sensor, wherein the processing arrangement is configured to receive the reflected waveform from the non-imaging sensor, employ a first neural network to estimate the skeletal pose of the subject, feed a temporal succession of a plurality of skeletal poses of the subject to a second neural network, and determine the activity performed by the subject based on the temporal succession of the plurality of skeletal poses. Disclosed also is a method for monitoring an activity performed by the subject.

A method for vascular assessment is disclosed. The method, in some embodiments, comprises receiving a plurality of 2-D angiographic images of a portion of a vasculature of a subject, and processing the images to produce a stenotic model over the vasculature, the stenotic model having measurements of the vasculature at one or more locations along vessels of the vasculature. The method, in some embodiments, further comprises obtaining a flow characteristic of the stenotic model, and calculating an index indicative of vascular function, based, at least in part, on the flow characteristic in the stenotic model.

A system and method is provided for processing a whole slide image, WSI, of a biopsy such as a core needle biopsy or a vacuum assisted biopsy. A skeleton of the shape of the detected tissue is created and a skeleton path is determined. An image is generated comprising a line representing the skeleton path with different line representations along the line representing different tissue pathologies. A pathology summary for the overall line is also prepared. This provides the information desired by a pathologist in a most convenient format and representation.

A model generation system generates three-dimensional (3D) models for objects based on two-dimensional (2D) images of the objects. The model generation system may receive object images and generate a 3D object model for the object based on the object image. The model generation system may generate an object skeleton for the object based on the object image. The model generation system may use the object skeleton to generate pixel partitions representing parallel cross sections of the object. The model generation system may apply a machine-learning model (e.g., a neural network) to the object image to determine parameters for a shape that would best represent each parallel cross section and then generate the 3D object model for the object based on the shapes of each cross section, the object image, and the object skeleton.

A length of a target portion is determined such that foot grounding property can be determined during a virtual test ride, and to easily determine a length equal to or approximate to an actual measured length of the target portion without using a sensor configured to directly detect an actual measured value. In an information processing device, a skeleton estimation unit estimates a skeleton of the service user, an information acquisition unit acquires attribute data including a body height of a service user, and a calculation unit calculates a first length equivalent to a first skeleton forming a part of the body height. The first length is obtained by subtracting, from the body height, a specified value and calculates each length of target portions (a leg, an arm, and a torso) of the service user using ratios among the skeletons in the estimated skeleton, and the first length.

Systems and methods use a three-dimensional snapshot of an infant, child, adolescent, or adult where the subject may have bent legs and an unaligned head position, to provide an estimate of human length. The system identifies anatomical features from the digital information and generates a virtual skeleton. The cumulative distances between pseudo-joints of the virtual skeleton provide an estimate of human length. Comparing length estimates from multiple three-dimensional snapshots of the same individual acquired over time provide an indication of growth of the infant, child, or adolescent. Daily estimates of length can detect growth faltering sooner than less frequent estimates of length, which can lead to timely intervention.

A video generation method includes: performing video shooting in response to a trigger operation for a video duet option; obtaining a second video currently shot, where the second video corresponds to a video clip including a target character in a first video; and fusing the second video into video content of the first video based on one or more characters recognized in the first video, to obtain a duet video, the one or more characters including the target character.

Various embodiments relate to a computer apparatus for the bone microstructure connectivity recovery of a skeletal image reconstructed through an artificial neural network using the representations of a node-link graph-based bone microstructure and a method thereof. The computer apparatus and the method may be configured to represent a node-link graph from a bone microstructure of an input skeletal image, reinforce a connectivity of the bone microstructure in the node-link graph, and change the node-link graph into a skeletal image.

Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing at least one program, and a method for performing operations comprising: receiving a video that depicts a person. The operations further include identifying a set of skeletal joints of the person. The operations further include identifying a pose of the person depicted in the video based on positioning of the set of skeletal joints (or detecting a hand pose, detecting a mirror frame, or detecting a mobile device). The operations further include determining, based on the pose of the person (or detecting a hand pose, detecting a mirror frame, or detecting a mobile device), that the video comprises a mirror reflection of the person. The operations further include, in response to determining that the video comprises the mirror reflection of the person, causing display of a 3D virtual object in the video.