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Multimedia Tools and Applications

, Volume 77, Issue 24, pp 31693–31712 | Cite as

A computer assisted automatic grenade throw training system with simple digital cameras

  • Bin Liu
  • Yubo Ma
  • Yu Pei
  • Chao Wang
  • Chao Wan
Article
  • 47 Downloads

Abstract

Grenade throwing is a routine military training and testing subject among many armies of the world. However, the conventional manual measurement mode has many defects: poor efficiency, large training field needing and important data losing. So how to utilize simple device and simple method framework to replace the actual test procedure becomes an interesting issue. In this paper, we present a real-time computer assisted grenade throwing training system by simple digital camera and low-cost computational methods. In this system, firstly, the marked grenade is extracted from the camera video frames; Secondly, a linked list is generated to store the grenade pixel coordinate; Thirdly, after a transformation from image space to real space, the instantaneous velocity of throwing (initial speed) can be computed; Lastly, a virtual 3D scene is established to demonstrate the training activity. By using this system, an overall throwing result data (distance, height, throwing angle, throwing speed and ballistic trajectory) can be obtained. The most significant novelty of our application is achieving a real-time computer assisted grenade throwing training system by simple and low-cost computational methods. In addition, we proposed a specialized self-adapted color enhancement method in the system. This computation strategy may provide some enlightenments for other research work. From the test data of several hurlers, it can be seen that the effectiveness and the accuracy of this training system are favorable. This system may provide technical support for the modern military throwing training and may change the traditional manual measuring mode for grenade throwing.

Keywords

Grenade throwing Military training Camera video frame Virtual 3D scene Real-time system 

Notes

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Nos. 61572101, 61300085), the Scientific Research Fund of Liaoning Provincial Education Department of China (No. L2013012) and the Fundamental Research Funds for the Central Universities of China (No. DUT14QY18). Thanks to Prof. Bingbing Zhang, Ms. Xiuyan Peng and Mr. Yuxiang Liu for providing training ground and training device and for help with camera calibration.

Supplementary material

11042_2018_6183_MOESM1_ESM.mp4 (13.5 mb)
ESM 1 (MP4 13813 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Bin Liu
    • 1
    • 2
  • Yubo Ma
    • 1
  • Yu Pei
    • 1
  • Chao Wang
    • 1
  • Chao Wan
    • 3
  1. 1.International School of Information Science & Engineering (DUT-RUISE)Dalian University of TechnologyDalianChina
  2. 2.Key Lab of Ubiquitous Network and Service Software of Liaoning ProvinceDalianChina
  3. 3.No.403 Clinical Department of PLA (People’s Liberation Army)DalianChina

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