Optical Flow-Based Marker Tracking Algorithm for Collaboration Between Drone and Ground Vehicle

KIPS Transactions on Software and Data Engineering, Vol. 7, No.3, pp.107-112, March 2018
10.3745/KTSDE.2018.7.3.107, Full Text

Abstract

In this paper, optical flow based keypoint detection and tracking technique is proposed for the collaboration between flying drone with vision system and ground robots. There are many challenging problems in target detection research using moving vision system, so we combined the improved FAST algorithm and Lucas-Kanade method for adopting the better techniques in each feature detection and optical flow motion tracking, which results in 40% higher in processing speed than previous works. Also, proposed image binarization method which is appropriate for the given marker helped to improve the marker detection accuracy. We also studied how to optimize the embedded system which is operating complex computations for intelligent functions in a very limited resources while maintaining the drone’s present weight and moving speed. In a future works, we are aiming to develop collaborating smarter robots by using the techniques of learning and recognizing targets even in a complex background.


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Cite this paper

[KIPS Transactions Style]
J. Beck and S. Kim, "Optical Flow-Based Marker Tracking Algorithm for Collaboration Between Drone and Ground Vehicle," KIPS Transactions on Software and Data Engineering, Vol.7, No.3, pp.107-112, 2018, DOI: 10.3745/KTSDE.2018.7.3.107.

[IEEE Style]
Jong-Hwan Beck and Sang-Hoon Kim, "Optical Flow-Based Marker Tracking Algorithm for Collaboration Between Drone and Ground Vehicle," KIPS Transactions on Software and Data Engineering, vol. 7, no. 3, pp. 107-112, 2018. DOI: 10.3745/KTSDE.2018.7.3.107.

[ACM Style]
Beck, J. and Kim, S. 2018. Optical Flow-Based Marker Tracking Algorithm for Collaboration Between Drone and Ground Vehicle. KIPS Transactions on Software and Data Engineering, 7, 3, (2018), 107-112. DOI: 10.3745/KTSDE.2018.7.3.107.