3D Model-Based Exercise Movement Evaluation System
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Solution Overview
Problem
Existing exercise support systems struggle to accurately evaluate movements of individuals due to the inability to specify which body part crosses a detection region, leading to inadequate evaluations.
Innovation Solution
The system employs multiple imaging devices to capture videos and generate 3D model data, comparing it to reference 3D model data to evaluate movements accurately, with features like body part information acquisition and reference 3D correction to standardize evaluations and provide feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple sensors are arranged surrounding the dance area with non-overlapped detection regions, then the detection coverage is improved, but the ability to specify which body part crosses the detection region deteriorates
Solution Approach 1:
The patent transitions from 2D sensor detection planes to 3D spatial modeling. Multiple imaging devices capture videos from different angles, and 3D model data is generated to represent the person's movements in three-dimensional space. This dimensional transformation enables precise identification of which body part crosses the detection region by visualizing and analyzing the 3D position and orientation of body parts throughout the movement sequence.
Solution Approach 2:
The patent introduces 3D model data as an intermediary between the raw video capture and the movement evaluation. The 3D model serves as a mediator that processes and interprets the video data from multiple imaging devices, enabling the system to identify specific body parts and their movements with high precision while maintaining comprehensive detection coverage through the coordinated use of multiple sensors.
2Measurement precision
If reference 3D model data is corrected to approximate the person's body shape, then the evaluation accuracy is improved, but the processing complexity increases
Solution Approach 1:
The patent dynamically adjusts parameters of the reference 3D model data to match the person's actual body shape characteristics. The reference 3D model is corrected by modifying parameters such as body dimensions, proportions, and anatomical features based on the captured video data and 3D model generation results. This parameter adjustment enables accurate evaluation tailored to each individual's body shape without requiring completely new evaluation models.
Solution Approach 2:
The system automatically performs the correction of reference 3D model data based on the captured video and generated 3D model information. The correction process is self-executing, using the person's own body shape data extracted from the video to adjust the reference model, thereby reducing the need for manual intervention or complex external processing while maintaining high evaluation accuracy.
Data Source
AI summary
An exercise support system includes a plurality of imaging devices, a 3D generation section, an evaluation reference memory, and an evaluation section. The imaging devices are configured to capture videos for movements of a person to be evaluated. The 3D generation section is configured to generate 3D model data of the person to be evaluated based on the video captured by each of the imaging devices. The evaluation reference memory is configured to store reference 3D model data that is 3D model data to become an evaluation reference of an exercise. The evaluation section is configured to evaluate the movements of the person to be evaluated by comparing between the reference 3D model data and the 3D model data generated by the 3D generation section in each body part of the person to be evaluated.