Research on Target Tracking and Early-Warning for the Safety of Coal Mine Production

Abstract:

In recent years, the technology of video surveillance, widely used in the coal industry, has become an important technical means in mine safety production and management. Movement monitoring of personnel and carrier is an important part in underground video monitoring and management. This paper firstly detects change region of moving targets through background subtraction and temporal difference. Detecting moving targets through binarization and morphological filtering, thus personnel and carrier are identified combining with shape feature and texture. The rest of this paper puts forward an improved particle filter method to recognize and track multiple moving targets. Lastly this paper gives an underground video example to monitor the underground video. The result of this paper shows that this method has great significance for mine safety production.

• Periodical: Applied Mechanics and Materials (Volumes 644-650)
• Pages: 925-929
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.644-650.925
• Online since: September 2014
• Authors: Zhan Li Li*, Ai Ling Xie
• Keywords: Particle Filter, Recognition, Tracking, Video Surveillance, Warning

References

[1] Dan Li. Research on Object Detection and Tracking Algorithm and Its Application in Coal Mine[D]. China University of Mining And Technology, (2011).

[2] Cheng Xu, Hong Bao, Lulu Zhang, Wei Liu. Progress in the Study of Vision-based Dynamic Object Recognition[J]. Journal of Beijing Union University. 2013. 27(4): 24-29.

[3] Shilin Wu, Feng Zhu. Multi-Class Object Recognition in Natural Scenes[J]. Computer Engineering & Science, 2012, 34(3): 91-95.

[4] Jian Yao, Jean-marc Odobez. Multi-camera 3D Person tracking with particle filter in a surveillance environment[J]. EUSIPCO, 2008: 25-29.

[5] Ben Niu. Design of Monocular Vision Based Anti-collision Warning System for the Tramcar[D]. Master's Degree Thesis of ChongQing University, (2009).

[6] Mingming Chen. Research on Vehicle Detection and Vehicle Types Recognition in Videos[D]. Nanjing University of Posts and Telecommunications, (2013).

[7] Ge Fan. The Research on Target Tracking Algorithm Based on Particle Filter[D]. Master's Degree Thesis of South China University of Technology, (2013).

[8] Huanyu Luo, Liaojun Lei, Zhonglin Mu. Tracking Framework for Small Infrared Multi-Target in Complex Background[J], Acta Optica Sinica, 2009, 29(6).

DOI: 10.3788/aos20092906.1536