Machine Learning for Visual Navigation of Unmanned Ground Vehicles

Autor:	Lenskiy, Artem A., Lee, Jong-Soo
Rok vydání:	2016
Předmět:	Computer Science - Computer Vision and Pattern Recognition I.4.7 I.4.8 I.5.1
Druh dokumentu:	Working Paper
DOI:	10.4018/978-1-60960-818-7.ch418
Popis:	The use of visual information for the navigation of unmanned ground vehicles in a cross-country environment recently received great attention. However, until now, the use of textural information has been somewhat less effective than color or laser range information. This manuscript reviews the recent achievements in cross-country scene segmentation and addresses their shortcomings. It then describes a problem related to classification of high dimensional texture features. Finally, it compares three machine learning algorithms aimed at resolving this problem. The experimental results for each machine learning algorithm with the discussion of comparisons are given at the end of the manuscript. Comment: Preprint of the chapter in the Machine Learning for Visual Navigation of Unmanned Ground Vehicles 2012
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1604.02485 Zobrazit plný text záznamu View this record from Arxiv