Motion Analysis System Using Non-Uniform Key Position Extraction
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Solution Overview
Problem
Existing motion analysis systems for sports and medical activities are inadequate for athletes who need to train and repeat precise key positions, as they fail to account for key positions that have no duration and are not equally spaced, leading to inefficient training and analysis.
Innovation Solution
A method that defines key positions in a sporting or medical activity, acquires video sequences, extracts still pictures corresponding to these positions, and displays them for analysis, using metadata and sensors to enhance the visualization of key moments, allowing for better execution and training.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If evenly spaced frames are extracted from video sequence, then stroboscopic effect is achieved, but key positions that are not equally spaced cannot be properly identified
Solution Approach 1:
The system pre-defines key positions based on sports-specific templates before video analysis. These templates specify the expected number, timing, and spatial distribution of key positions for different sports activities, enabling the system to extract frames at predetermined non-uniform intervals rather than evenly spaced intervals
Solution Approach 2:
The system dynamically adjusts frame extraction parameters based on the defined key positions. Instead of using fixed time intervals, the system calculates optimal extraction intervals based on the temporal distribution of key positions in the sport activity, allowing for non-uniform sampling that captures critical moments accurately
2Loss of information
If multiple still pictures are extracted and displayed, then comprehensive motion analysis is provided, but many similar pictures of little interest are produced
Solution Approach 1:
The system extracts only the essential information by selectively capturing still pictures at pre-defined key positions rather than extracting all frames or using uniform sampling. This extraction approach removes redundant information (similar pictures of little interest) while preserving critical motion data at meaningful moments
Solution Approach 2:
The system applies different analysis qualities to different parts of the motion sequence. By focusing computational resources and extraction attention on specific key positions that are most important for the sport activity, the system provides high-quality analysis where needed while minimizing unnecessary processing and output for less critical moments
3Measurement precision
If key positions are defined for training, then precise motion analysis is enabled, but the system is not adapted for athletes who want to train and repeat particular motions
Solution Approach 1:
The system is designed to serve multiple functions: it can analyze existing video sequences to identify key positions, provide training guidance by comparing athletes' performances against predefined templates, and offer feedback for repetition practice. This multi-functionality makes the system adaptable to both analysis and training scenarios
Solution Approach 2:
The system provides feedback to athletes by comparing their performed motion against the predefined key positions and templates. This feedback mechanism enables athletes to understand their deviations from optimal performance and adjust their repetitions accordingly, making the system highly useful for training purposes
Data Source
AI summary
A method is disclosed for analyzing with a computer (1) the motion of an athlete (3), of a team or a patient during an activity, said method comprising the steps of defining a number of unevenly time-spaced key positions in said motion, said key positions being of particular interest for analyzing the correct execution of said motion by said athlete (3) or team. A video sequence (11) of said motion is acquired with a camera (2) and still pictures (12) are extracted from said video sequence (11). Templates can trigger the automatic extraction of still pictures (12). For extraction purposes, a metadata recorded with a sensor (5) at the same time as the video sequence (11) can be used. Said still pictures (12) correspond to said previously defined key positions. Thereafter said extracted still pictures (12) are displayed simultaneously on a same display (10).