ArticleSensors (Basel, Switzerland)2021
Student Behavior Recognition System for the Classroom Environment Based on Skeleton Pose Estimation and Person Detection.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Classroom Behavior Recognition Using Computer Vision: A Systematic Review.Sensors (Basel, Switzerland) · 2025Pooled it
- Enhancing classroom behavior analysis with multimodal data: a cross-attention fusion network approach.Scientific reports · 2026Article
- Human Activity Recognition with Noise-Injected Time-Distributed AlexNet.Biomimetics (Basel, Switzerland) · 2025Article
- Classroom Behavior Detection Method Based on PLA-YOLO11n.Sensors (Basel, Switzerland) · 2025Article
- CSSA-YOLO: Cross-Scale Spatiotemporal Attention Network for Fine-Grained Behavior Recognition in Classroom Environments.Sensors (Basel, Switzerland) · 2025Article
- A WAD-YOLOv8-based method for classroom student behavior detection.Scientific reports · 2025Article
- YOLO-AMM: A Real-Time Classroom Behavior Detection Algorithm Based on Multi-Dimensional Feature Optimization.Sensors (Basel, Switzerland) · 2025Article
- IMRMB-Net: A lightweight student behavior recognition model for complex classroom scenarios.PloS one · 2025Article
- A Dynamic Position Embedding-Based Model for Student Classroom Complete Meta-Action Recognition.Sensors (Basel, Switzerland) · 2024Article
- Integrating OpenPose and SVM for Quantitative Postural Analysis in Young Adults: A Temporal-Spatial Approach.Bioengineering (Basel, Switzerland) · 2024Article
- Student Behavior Analysis using YOLOv5 and OpenPose in Smart Classroom Environment.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Fast Three-Dimensional Posture Reconstruction of Motorcyclists Using OpenPose and a Custom MATLAB Script.Sensors (Basel, Switzerland) · 2023Article
- SSA Net: Small Scale-Aware Enhancement Network for Human Pose Estimation.Sensors (Basel, Switzerland) · 2023Article
- Research on Safety Helmet Detection Algorithm Based on Improved YOLOv5s.Sensors (Basel, Switzerland) · 2023Article
- MSTA-SlowFast: A Student Behavior Detector for Classroom Environments.Sensors (Basel, Switzerland) · 2023Article
- Multi-view and multi-scale behavior recognition algorithm based on attention mechanism.Frontiers in neurorobotics · 2023Article
- Towards automated video-based assessment of dystonia in dyskinetic cerebral palsy: A novel approach using markerless motion tracking and machine learning.Frontiers in robotics and AI · 2023Article
- Pose Mask: A Model-Based Augmentation Method for 2D Pose Estimation in Classroom Scenes Using Surveillance Images.Sensors (Basel, Switzerland) · 2022Article
- Identifying the Posture of Young Adults in Walking Videos by Using a Fusion Artificial Intelligent Method.Biosensors · 2022Article
- Recognition of students' abnormal behaviors in English learning and analysis of psychological stress based on deep learning.Frontiers in psychology · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Human action recognition has attracted considerable research attention in the field of computer vision, especially for classroom environments. However, most relevant studies have focused on one specific behavior of students. Therefore, this paper proposes a student behavior recognition system based on skeleton pose estimation and person detection. First, consecutive frames captured with a classroom camera were used as the input images of the proposed system. Then, skeleton data were collected using the OpenPose framework. An error correction scheme was proposed based on the pose estimation and person detection techniques to decrease incorrect connections in the skeleton data. The preprocessed skeleton data were subsequently used to eliminate several joints that had a weak effect on behavior classification. Second, feature extraction was performed to generate feature vectors that represent human postures. The adopted features included normalized joint locations, joint distances, and bone angles. Finally, behavior classification was conducted to recognize student behaviors. A deep neural network was constructed to classify actions, and the proposed system was able to identify the number of students in a classroom. Moreover, a system prototype was implemented to verify the feasibility of the proposed system. The experimental results indicated that the proposed scheme outperformed the skeleton-based scheme in complex situations. The proposed system had a 15.15% higher average precision and 12.15% higher average recall than the skeleton-based scheme did.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.