基于Rényi散度最大化的多特征闭环检测

doi:10.16451/j.cnki.issn1003-6059.201805001

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Abstract Multiple image features provide more discriminative information of the scenes compared with individual feature, and thus the performance of loop closure detection(LCD) is improved. However, a suitable combination criterion is vital. A weighting method of multiple feature combination is proposed. The accuracy of LCD of the feature combination is expressed as the Rényi divergence of the distance distributions of true matches and false matches in the feature space. The optimal feature combination maximizes the Rényi divergence. The relationship between the parameter of Rényi divergence and the performance of LCD of the optimal feature combination is analyzed and experimentally verified. The experiments show that the proposed method improves the performance of LCD significantly and the best performance is achieved with the parameter of Rényi divergence being from 0.75 to 1.

Key words： Simultaneous Localization and Mapping(SLAM) Loop Closure Detection Simultaneous Localization and Mapping(SLAM) Illumination Variation Loop Closure Detection Feature Combination Illumination Variation Rényi Divergence Feature Combination Rényi Divergence

Received: 15 January 2018

ZTFLH:

TP 391.4

Corresponding Authors: WANG Xiaolong, Ph.D. candidate. His research interests include visual loop closure detection and visual SLAM.

About author:: PENG Guohua, Ph.D., professor. His research interests include image processing and computer aided geometric design

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Cite this article:

PENG Guohua,WANG Xiaolong,PENG Guohua. Loop Closure Detection Based on Maximizing Rényi Divergence of Multiple Features[J]. , 2018, 31(5): 389-397.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201805001 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2018/V31/I5/389

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