Real Time Kinematic Analyses of Body Motion

Number: 20230069401
Published: 2023-03-02
Filed: 2022-10-24
Assignee: Disney Enterprises, Inc.
Inventors: Prince; Kevin John et al.
CPC: G06F18/23; G06T7/251; G06T7/55; G06V10/762; G06V20/42; G06V20/44; G06V40/23; G06V40/28
Verdict: Low Notable software
Source: Google Patents · FreePatentsOnline

The keeper's note

Real-time kinematic body-motion analysis technique.

Abstract

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.

Background

BACKGROUND

Professional games, such as combat sports, generate an abundance of information that is hard for viewers to follow and appreciate in real time. For example, in a boxing match, the occurrence of a play action carried out by a player (such as a jab, a cross, an undercut, or a hook) as well as the play action's forcefulness and effectiveness may be hard for a viewer to immediately recognize and quantify by mere visual inspection of the player's performance during the game. Likewise, comparative and cumulative analyses of the movements of performing participants during a live event cannot be accomplished without an automated system. Analyses of the live event's video to detect and to measure the participants' performances, can facilitate statistics in real time. In a sporting event, for example, game statistics, generated as the game unfolds, may support commentary and may provide insights into the development of the game by intuitive visualization of the game statistics.

Analyzing a live event to detect play actions performed by participants of the event requires techniques for real time detection of actions of interest, employable on video feeds that capture the live event. Various action recognition techniques have been proposed for applications such as human-machine interfaces, video indexing and retrieval, video surveillance, and robotics, for example. However, detecting play actions in real time, that by their nature are of high motion and spatiotem

Claims

21. A method comprising: receiving a first sequence of positional data associated with a first performance of a first participant in an event; receiving a second sequence of positional data associated with a second performance of a second participant in the event; detecting, based the first sequence of positional data and the second sequence of positional data, movements of the first participant and the second participant; and determining, based on the movements of the first participant and the second participant, a collision between the first participant and the second participant. || 30. An apparatus comprising: a processor; and a memory storing instructions that, when executed by the processor, cause the apparatus to: receive a first sequence of positional data associated with a first performance of a first participant in an event; receive a second sequence of positional data associated with a second performance of a second participant in the event; detect, based the first sequence of positional data and the second sequence of positional data, movements of the first participant and the second participant; and determine, based on the movements of the first participant and the second participant, a collision between the first participant and the second participant. || 39. A method comprising: receiving a sequence of positional data associated with a performance of a participant in an event; detecting, based on the sequence of positional data, one or more actions performed by the participant; measuring, based on the detected one or more actions, an energy exerted by the participant; and generating statistics based on the measured energy exerted by the participant.