3D Sensing Video Extraction for Athletic Scoring Precision
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional technologies fail to extract videos based on scores from series of videos related to scoring competitions, limiting the ability to identify and highlight specific scoring moments effectively.
Innovation Solution
An extraction program that utilizes 3D sensing data to determine the success or failure and perfection level of athletic elements, generating and outputting videos of specific scenes from 3D model moving images and video captures, allowing for the extraction of videos based on scoring criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional video extraction methods using index information are used, then videos of specific scenes can be extracted, but the ability to extract videos based on scoring criteria and perfection levels is limited
Solution Approach 1:
The patent introduces 3D sensing data as an intermediary between the video content and the extraction process. This intermediary enables the system to detect and extract videos based on scoring criteria and perfection levels by providing precise measurement data about athlete positions, movements, and performance metrics that conventional index information cannot capture.
2Measurement precision
If 3D sensing data is used to determine success or failure and perfection level, then scoring accuracy is improved, but system complexity increases
Solution Approach 1:
The patent replaces manual scoring and conventional video analysis methods with 3D sensing technology. This substitution automates the detection of athlete positions, movements, and performance metrics, enabling objective and precise scoring while reducing human subjectivity and manual analysis complexity.
Solution Approach 2:
The patent transforms physical performance parameters (athlete positions, movements, speeds) into measurable 3D sensing data parameters. By changing the representation of performance metrics from subjective visual assessment to quantifiable 3D coordinates and movement vectors, the system achieves higher measurement precision.
3Manufacturing precision
If multiple determination criteria (success/failure and perfection level) are used, then extraction accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary processing of 3D sensing data to pre-calculate athlete positions, movements, and performance metrics during the performance itself. This preliminary action enables the system to quickly determine success or failure and perfection levels without requiring time-consuming post-analysis, thus maintaining high extraction accuracy while reducing processing time.
Data Source
AI summary
An information processing apparatus (100) extracts, from among a plurality of elements, a first element that falls within a predetermined range from a first reference for determination of success or failure or a second element that falls within a predetermined range from a second reference for determination of a perfection level, on the basis of at least one of a determination result of the success or failure and a determination result of the perfection level. The information processing apparatus (100) extracts a portion corresponding to the first element or the second element from a 3D model moving image that is generated from 3D sensing data of a series of performances of the athlete or a video that is obtained by capturing the performances, and outputs the extracted moving image or the extracted video.