Research on Visual Place Recognition Algorithms for Complex Urban Environments

Authors

• Peijin Liu, School of Mechatronic Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
• Minxin Zhang, School of Mechatronic Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
• Lin He, School of Science, Xi'an University of Architecture and Technology, Xi'an 710055, China
• Yige Sun, School of Mechatronic Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
• Tingqi Su, School of Mechatronic Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China

Abstract

Abstract: Dynamic factors such as traffic flow and crowd density in complex urban environments reduce the accuracy of visual place recognition (VPR) algorithms. To solve these problems, a semantic-guided visual place recognition (SG-VPR) algorithm was proposed. A semantic-guided feature suppression module was designed. A semantic-guided module and feature suppression layer were constructed to reduce the dynamic object interference and more accurately extract the key static features. An adaptive triplet margin loss function (ATML) was proposed by improving the traditional triplet margin loss. The margins were adaptively adjusted according to the sample distribution, solving the problem of suboptimal solution convergence caused by a fixed margin strategy and improving the feature differentiation ability. Experimental results show that the SG-VPR outperforms existing methods on the Pittsburgh250k and Tokyo24/7 public datasets with complex urban environments, especially in coping with dynamic interference scenarios, which significantly improves the performance of the VPR algorithm.

Recommended Citation

Liu, Peijin; Zhang, Minxin; He, Lin; Sun, Yige; and Su, Tingqi (2026) "Research on Visual Place Recognition Algorithms for Complex Urban Environments," Journal of System Simulation: Vol. 38: Iss. 3, Article 21.
DOI: 10.16182/j.issn1004731x.joss.25-0031
Available at: https://dc-china-simulation.researchcommons.org/journal/vol38/iss3/21

First Page

818

Last Page

828

CLC

TP391.9

Recommended Citation

Liu Peijin, Zhang Minxin, He Lin, et al. Research on Visual Place Recognition Algorithms for Complex Urban Environments[J]. Journal of System Simulation, 2026, 38(3): 818-828.

Corresponding Author

He Lin

DOI

10.16182/j.issn1004731x.joss.25-0031