A survey on recent object detection techniques useful for monocular vision-based planetary terrain classification

被引:32
作者
Gao, Yang [1 ]
Spiteri, Conrad [1 ]
Minh-Tri Pham [1 ]
Al-Milli, Said [1 ]
机构
[1] Univ Surrey, Surrey Space Ctr, Guildford GU2 5XH, Surrey, England
基金
英国工程与自然科学研究理事会;
关键词
Remote terrain classification; Autonomous navigation; Object detection; Monocular vision; Planetary rovers; HAAR-LIKE FEATURES; FACE DETECTION; PEDESTRIAN DETECTION; TRACKING; NETWORK; IMAGES; MULTIPLE; TEXTURE; VIEW; COMBINATION;
D O I
10.1016/j.robot.2013.11.003
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Direct terrain classification from monocular images for autonomous navigation of planetary rovers is a relatively new and challenging research area, not only because of the hardware limitation of a rover, but also because the rocks and obstacles to be detected exhibit diverse morphologies and have no uniform properties to distinguish them from background soil. We present a survey of recently developed object detection techniques that can be useful for terrain classification for planetary rovers. We start with summarizing current vision-based terrain classification methods. We then provide a comprehensive and structured overview of recent object detection techniques, focusing on those applicable to terrain classification. Crown Copyright (C) 2013 Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:151 / 167
页数:17
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