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Real-Time Visual Place Recognition Based on Analyzing Distribution of Multi-scale CNN Landmarks

文献类型：期刊论文

作者Xin, Zhe1,2; Cui, Xiaoguang1; Zhang, Jixiang1; Yang, Yiping1; Wang, Yanqing1
刊名JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
出版日期2019-06-01
卷号94期号:3-4页码:777-792
ISSN号0921-0296
关键词Visual place recognition Localization Convolutional neural networks Changing environments Landmark distribution 68T45 92B20
DOI10.1007/s10846-018-0804-x
通讯作者Xin, Zhe(xinzhe2015@ia.ac.cn)
英文摘要What makes visual place recognition difficult to solve is the variation of the real-world places. In this work, an effective similarity measurement is proposed for visual place recognition in changing environments, based on Convolutional Neural Networks (CNNs) and content-based multi-scale landmarks. The image is firstly segmented into multi-scale landmarks with content information in order to adapt variations of viewpoint, then highly representative features of landmarks are derived from Convolutional Neural Networks (CNNs), which are robust against appearance variations. In the similarity measurement, the similarity between images is determined by analyzing both spatial and scale distributions of matched landmarks. Moreover, an efficient feature extraction and reduction strategy are proposed to generate all features of landmarks at one time. The efficiency of the proposed method makes it suitable for real-time applications. The proposed method is evaluated on two widespread datasets with varied viewpoint and appearance conditions and achieves superior performance against four other state-of-the-art methods, such as the bag-of-words model DBoW3 and the CNN-based Edge Boxes landmarks. Extensive experimentation demonstrates that integrating global and local information can provide more invariance in severe appearance changes, and considering the spatial distribution of landmarks can improve the robustness against viewpoint changes.
WOS关键词FEATURES ; SCALE
WOS研究方向Computer Science ; Robotics
语种英语
出版者SPRINGER
WOS记录号WOS:000468432500015
源URL[http://ir.ia.ac.cn/handle/173211/24212]  
专题综合信息系统研究中心_视知觉融合及其应用
通讯作者Xin, Zhe
作者单位1.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Xin, Zhe,Cui, Xiaoguang,Zhang, Jixiang,et al. Real-Time Visual Place Recognition Based on Analyzing Distribution of Multi-scale CNN Landmarks[J]. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS,2019,94(3-4):777-792.
APA Xin, Zhe,Cui, Xiaoguang,Zhang, Jixiang,Yang, Yiping,&Wang, Yanqing.(2019).Real-Time Visual Place Recognition Based on Analyzing Distribution of Multi-scale CNN Landmarks.JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS,94(3-4),777-792.
MLA Xin, Zhe,et al."Real-Time Visual Place Recognition Based on Analyzing Distribution of Multi-scale CNN Landmarks".JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 94.3-4(2019):777-792.

入库方式： OAI收割

来源：自动化研究所

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