A multi-feature integrated visual attention model for matching-area suitability analysis in visual navigation

Zhenlu Jin, Quan Pan, Chunhui Zhao, Huixia Liu, Wei Jia

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

For matching-area suitability analysis of unmanned aerial vehicle (UAV) visual navigation, a multi-feature integrated visual attention model (MFI-VAM) was established by introducing invariant features, based on which the extraction method of suitable matching-area was proposed. Speeded-up robust features (SURF) were added into visual attention model. The conspicuity map of SURF channel is obtained by cross-scale feature maps integration. Based on multi-feature fusion of SURF, color, intensity and orientation, the MFI-VAM model was built. Salient locations in current map were chosen as suitable matching-areas based on this model. Simulation results show that the image registration error of extracted matching-area based on proposed method is small. This paper could provide new ideas and theoretical guidance for UAV autonomous navigation.

源语言英语
主期刊名Proceedings of the 32nd Chinese Control Conference, CCC 2013
出版商IEEE Computer Society
5122-5127
页数6
ISBN(印刷版)9789881563835
出版状态已出版 - 18 10月 2013
活动32nd Chinese Control Conference, CCC 2013 - Xi'an, 中国
期限: 26 7月 201328 7月 2013

出版系列

姓名Chinese Control Conference, CCC
ISSN(印刷版)1934-1768
ISSN(电子版)2161-2927

会议

会议32nd Chinese Control Conference, CCC 2013
国家/地区中国
Xi'an
时期26/07/1328/07/13

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