Research on Video Tracking System Method Based on Classroom 
Teaching

Wei Zhang; Shuzhou Chai; Gaohua Liu; Hansong Su

doi:10.18686/modern-management-forum.v8i6.13250

Research on Video Tracking System Method Based on Classroom Teaching

Wei Zhang, Shuzhou Chai, Gaohua Liu, Hansong Su

Abstract

In response to the problem of video tracking in classroom teaching, a video tracking system using optical fl ow method
improvement method is proposed. Using the processing functions provided by OpenCV, analyze the states of teachers and students in the
classroom, obtain their motion states, and then instruct the camera to track close-up or switch panoramic views. Using LK optical fl ow
method to analyze students’ motion state; Using clustering algorithms to calculate the number of students standing up; Using spatial analogy
method, calculate the position of the close-up student and indicate the rotation of the camera. This system has high practical value and
special signifi cance for online teaching, online classrooms, etc.

Keywords

OpenCV; LK optical fl ow method; Clustering algorithm; Analogy method

Full Text:

PDF

Included Database

References

[1] Yiguo Zhao. Research on Moving Object Detection and Tracking Technology in Classroom Video Recording System [D]. Nanjing: Nanjing University of

Posts and Telecommunications, 2015.

[2] Yi Liu, Mengmeng Li, et al. Overview of Video Object Tracking Algorithms [J]. Computer Science and Exploration, 2022, 16 (07): 1504-1515.

[3] Yin Chen. Research on Detection and Tracking Methods of Aerial Moving Targets [D] University of Electronic Science and Technology of China, 2023.

[4] Wenfeng Guo. Research on Motion Target Tracking Based on Machine Vision [D]. Guangdong: South China University of Technology, 2012.

[5] Ziyun Lu. Research on Optical Flow Field Calculation and Several Optimization Techniques [D]. Hefei: Hefei University of Technology, 2012.

[6] Yibo Cui, et al. Visual Optical Flow Computing Technology and Its Applications [J]. Journal of Electronics and Information Technology, 2023, 45 (08):

2710-2721.

[7] Sha Xiao. Research on Video Motion Object Detection Method Based on Frame Diff erence and Background Diff erence [D]. Hainan University, May 2015.

[8] Haiming Li, Xin Chen, et al. Optical fl ow region extraction method for moving targets in complex backgrounds [J]. Journal of Fuzhou University, 2014 (4):

101-104.

[9] Liya Su. Research on Particle Filter based Moving Target Tracking Algorithm [D]. Tianjin University of Technology, March 2014.

[10] Kai Wang. Research and Implementation of Scale Adaptive Motion Target Tracking Algorithm Integrating Kalman Filter and Mean Shift [D]. University

of Electronic Science and Technology of China, June 2013.

[11] Qiaona Pei. Research on Moving Object Detection and Tracking Based on Improved Optical Flow Method [D] Guangxi University, 2018.

[12] Kun Wu, Xiaohua Wang, Jinliang Yao. Copy Image Detection of Chi Tomasi Corner Region [J]. Journal of China Institute of Metrology, 2014 (3): 263-

267.

[13] Shaorong Feng, Wenjun Xiao. Research and Improvement of DBSCAN Clustering Algorithm [J]. Journal of China University of Mining and Technology,

2008, 37 (1): 105-111.

[14] Bo Yang. Research on Motion Object Detection and Tracking Algorithms in Video Image Sequence [D]. Lanzhou University of Technology, 2020.

[15] Haopeng Zhang. et al. A Tracking and Registration Method for Augmented Reality Assembly Systems Based on Image Matching [J]. Computer

Integrated Manufacturing Systems, 2021, 27 (05): 1281-1291.

DOI: http://dx.doi.org/10.18686/modern-management-forum.v8i6.13250

Refbacks

There are currently no refbacks.