The present disclosure relates to systems and methods for analyzing and evaluating movement of a subjects and providing feedback. In some embodiments, a method comprises receiving one or more images of a body of the subject captured during performance of a physical movement by the subject; computing a model descriptive of positions and orientations of body parts of the subject based on the one or more images; generating a comparison of the positions and orientations to target positions and target orientations, respectively, for the physical movement; and generating a recommendation based on the comparison.

Systems and methods create and distribute addressable virtual content with interactivity. The virtual content may depict a live event and may be customized for each individual user based on dynamic characteristics (e.g., habits, preferences, etc.) of the user that are captured during user interaction with the virtual content. The virtual content is generated with low latency between the actual event and the live content that allows the user to interactively participate in actions related to the live event. The virtual content may represent a studio with multiple display screens that each show different live content (of the same or different live events), and may also include graphic displays that include related data such as statistics corresponding to the live event, athletes at the event, and so on. The content of the display screens and graphics may be automatically selected based on the dynamic characteristics of the user.

Highly accurate shape registration processing is performed. In the image processing apparatus, data, which correspond to N frames (N is an integer not less than 2), in units of frames including a plurality of three-dimensional models per frame is acquired. Then, shape registration processing is performed for the acquired three-dimensional models corresponding to the N frames by using information indicating a correspondence relationship of the three-dimensional models between frames of the N frames.

Systems and methods for providing a distortion-free pool-surface display beneath a swimmer. In one embodiment, projectors are positioned below a water level at opposite walls of a pool, and are configured to project images to a display surface at the bottom of the pool beneath a swimmer. A camera is used to view images projected by the projectors and to provide corresponding image data to an image correction platform on a graphics processing unit (GPU). The image correction platform identifies distortions in the images, generates image corrections that counter the identified distortions, and applies the corrections to subsequently projected images. The image correction platform also generates image adjustment that cause overlapping portions of the projected images to match seamlessly. The projected images may provide immersive experiences, coaching/training interfaces or other interactive displays.

In various embodiments, a Data Processing System for Generating Interactive User Interfaces and Interactive Game Systems Based on Spatiotemporal Analysis of Video Content may be configured to: (1) enable a user to select one or more players participating in a substantially live (e.g., live) sporting or other event; (2) determine scoring data for each of the one or more selected players during the sporting or other event; (3) track the determined scoring data; (4) generate a custom (e.g., to the user) user interface that includes the scoring data; and (5) display the custom user interface over at least a portion of a display screen (e.g., on a mobile computing device) displaying one or more video feeds of the sporting or other event. In this way, the system may be configured to convert a video feed of a sporting event into an interactive game.

Disclosed is an exercise posture correction assistance method using working muscle information depending on motion performed by at least one server, including acquiring first image information containing movement of a user corresponding to a specific practice motion from a user terminal, deriving skeleton information corresponding to the movement of the user based on the first image information, generating second image information by indicating the movement of the user using a skeleton shape based on the first image information and the skeleton information, deriving muscle information corresponding to the specific practice motion from a database, generating muscle movement image information corresponding to the movement of the user based on the skeleton information and the muscle information, and providing the second image information and the muscle movement image information to the user terminal.

An information processing apparatus includes a definition processing unit that performs definition processing on feature amount information regarding a subject specified from an image. Therefore, for example, feature amount information such as posture information can be obtained with high accuracy.

Examples disclosed herein may generate a refined and denoised body pose data from a video feed of a sporting event. Tracking data containing player locations may be used to determine correspondence between a location and a body pose. For example, body pose with middle of key footpoints with shortest distance from the location may be selected as a likely body pose for the location. The body pose data may be refined to estimate the length of missing limbs or limbs with unusual length ratios. The body pose data may further be filtered to filter out unwanted body poses such as body poses of spectators or noisy body poses. The refined and filtered body pose data may be used for other downstream processing such as projecting the body poses to a three dimensional play surface.

Examples disclosed herein may estimate locations of players not visible in a sporting broadcast video. A prediction model may be generated based on a training data set of in-venue tracking data that includes locations of all players at all times and the corresponding broadcast tracking data that may not necessarily contain the locations of all players at all times. The prediction model may be based on an algorithmic logic (e.g., a spline regression) or machine learning model (e.g., k-nearest neighbor, deep neural network). The generated predicted model may be used to estimate the unknown locations of players in broadcast tracking based on the known locations.

A system including a computing device and camera is disclosed; the system configured for measuring three-dimensional attributes and associated performance measurements of a mechanical device. Some embodiments comprise a camera configured to capture images of the mechanical device and a computing device in communication with the camera. In some embodiments, the computing device is configured to access a first set of pixels associated with a first plurality of fiducials to calibrate a spatial resolution of the camera. A second image from the camera can be converted into a second set of pixels associated with each of the plurality of fiducials, which are attached to the mechanical device. The computing device can be further configured to compare the first and second set of pixels to determine the location of the plurality of fiducials on the mechanical device.