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Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

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An Interactive Human-in-the-Loop Framework for Skeleton-Based Posture Recognition in Model Education.

Jing Shen¹, Ling Chen¹, Xiaotong He²

¹College of Engineering and Design, Hunan Normal University, Changsha 410081, China.

Biomimetics (Basel, Switzerland)

|July 25, 2025

Summary

This summary is machine-generated.

This study introduces an interactive framework for skeleton-based posture recognition, enhancing model training and artistic education. The Transformer model achieved 92.7% accuracy, improving pose classification and educational support.

Keywords:

deep learning human pose estimation human-in-loop-control intelligent teaching system skeleton-based posture recognition

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Published on: August 30, 2016

Area of Science:

Computer Vision
Machine Learning
Educational Technology

Background:

Skeleton-based posture recognition is crucial for human-computer interaction and education.
Existing methods often lack interactivity and direct application in educational settings.

Purpose of the Study:

To develop a human-in-the-loop interactive framework for skeleton-based posture recognition.
To support model training and provide interactive feedback for artistic education.

Main Methods:

Extracted comprehensive skeletal features (joint coordinates, angles, limb lengths, symmetry).
Compared traditional (KNN, SVM, Random Forest) and deep learning (LSTM, Transformer) classification algorithms.
Integrated posture recognition with a visual recommendation module for educational feedback.

Main Results:

Deep learning models, particularly the Transformer, showed superior accuracy (92.7%) on complex postures.
Traditional models performed competitively with low-dimensional features.
The integrated system enhanced teaching interactivity and efficiency through semi-automated feedback.

Conclusions:

The proposed closed-loop framework effectively supports pose classification and model training.
The system offers algorithmic insights and a novel application for posture-driven educational support.
This interactive approach improves the learning process in artistic education.