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Sensors 2018, 18(1), 178; doi:10.3390/s18010178

Accurate Natural Trail Detection Using a Combination of a Deep Neural Network and Dynamic Programming

Division of Electronics Engineering, Chonbuk National University, Jeonju 567-54896, Korea
Institute of Applied Computer Science, Lodz University of Technology, Stefanowskiego 18/22, 90-924 Lodz, Poland
Intelligent Robot Research Center of Chonbuk National University, Chonbuk National University, Jeonju 567-54896, Korea
Both authors contributed equally to this work.
Author to whom correspondence should be addressed.
Received: 18 October 2017 / Revised: 20 December 2017 / Accepted: 4 January 2018 / Published: 10 January 2018
(This article belongs to the Section Physical Sensors)
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This paper presents a vision sensor-based solution to the challenging problem of detecting and following trails in highly unstructured natural environments like forests, rural areas and mountains, using a combination of a deep neural network and dynamic programming. The deep neural network (DNN) concept has recently emerged as a very effective tool for processing vision sensor signals. A patch-based DNN is trained with supervised data to classify fixed-size image patches into “trail” and “non-trail” categories, and reshaped to a fully convolutional architecture to produce trail segmentation map for arbitrary-sized input images. As trail and non-trail patches do not exhibit clearly defined shapes or forms, the patch-based classifier is prone to misclassification, and produces sub-optimal trail segmentation maps. Dynamic programming is introduced to find an optimal trail on the sub-optimal DNN output map. Experimental results showing accurate trail detection for real-world trail datasets captured with a head mounted vision system are presented. View Full-Text
Keywords: deep neural networks; trail segmentation; trail following; dynamic programming deep neural networks; trail segmentation; trail following; dynamic programming

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Adhikari, S.P.; Yang, C.; Slot, K.; Kim, H. Accurate Natural Trail Detection Using a Combination of a Deep Neural Network and Dynamic Programming. Sensors 2018, 18, 178.

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