典型文献
Illumination robust image transformations for feature-based SLAM using photometric and feature matches loss
文献摘要：
Simultaneous localization and mapping(SLAM)technology becomes more and more important in robot localization.The purpose of this paper is to improve the robustness of visual features to lighting changes and increase the recall rate of map re-localization under different lighting environments by optimizing the image transformation model.An image transformation method based on matches and photometric error(name the method as MPT)is proposed in this paper,and it is seamlessly integrated into the pre-processing stage of the feature-based visual SLAM framework.The results of the experiment show that the MPT method has a better matching effect on different visual features.In addition,the image transformation module encapsulated by a robot operating system(ROS)can be used with multiple visual SLAM systems and improve its re-localization effect under different lighting environments.
文献关键词：
中图分类号：
作者姓名：
Zhang Miao;Wang Zixian;Yan Danfeng
作者机构：
School of Computer Science,Beijing University of Posts and Telecommunications,Beijing 100876,China
文献出处：
引用格式：
[1]Zhang Miao;Wang Zixian;Yan Danfeng-.Illumination robust image transformations for feature-based SLAM using photometric and feature matches loss)[J].中国邮电高校学报（英文版）,2022(03):92-104
A类：
B类：
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AB值：
0.507428
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