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An Improved Optical Flow Algorithm Based on Mask-R-CNN and K-Means for Velocity Calculation

1
Key Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, School of Instrument and Electronics, North University of China, Taiyuan 030051, China
2
College of Energy & Electric Engineering, Hohai University, Nanjing 210098, China
*
Author to whom correspondence should be addressed.
Yahui Peng and Xiaochen Liu have the equal contribution to this work.
Appl. Sci. 2019, 9(14), 2808; https://doi.org/10.3390/app9142808
Received: 13 April 2019 / Revised: 4 July 2019 / Accepted: 11 July 2019 / Published: 13 July 2019
(This article belongs to the Section Applied Industrial Technologies)
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Abstract

Aiming at enhancing the accuracy and reliability of velocity calculation in vision navigation, an improved method is proposed in this paper. The method integrates Mask-R-CNN (Mask Region-based Convolutional Neural Network) and K-Means with the pyramid Lucas Kanade algorithm in order to reduce the harmful effect of moving objects on velocity calculation. Firstly, Mask-R-CNN is used to recognize the objects which have motions relative to the ground and covers them with masks to enhance the similarity between pixels and to reduce the impacts of the noisy moving pixels. Then, the pyramid Lucas Kanade algorithm is used to calculate the optical flow value. Finally, the value is clustered by the K-Means algorithm to abandon the outliers, and vehicle velocity is calculated by the processed optical flow. The prominent advantages of the proposed algorithm are (i) decreasing the bad impacts to velocity calculation, due to the objects which have relative motions; (ii) obtaining the correct optical flow sets and velocity calculation outputs with less fluctuation; and (iii) the applicability enhancement of the optical flow algorithm in complex navigation environment. The proposed algorithm is tested by actual experiments. Results with superior precision and reliability show the feasibility and effectiveness of the proposed method for vehicle velocity calculation in vision navigation system. View Full-Text
Keywords: velocity calculation; optical flow; pyramid LK; Mask-R-CNN; clustering algorithm velocity calculation; optical flow; pyramid LK; Mask-R-CNN; clustering algorithm
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Peng, Y.; Liu, X.; Shen, C.; Huang, H.; Zhao, D.; Cao, H.; Guo, X. An Improved Optical Flow Algorithm Based on Mask-R-CNN and K-Means for Velocity Calculation. Appl. Sci. 2019, 9, 2808.

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