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Published on: December 15, 2023
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Visual Place Recognition Based on Dynamic Difference and Dual-Path Feature Enhancement.
Guogang Wang1, Yizhen Lv1, Lijie Zhao1
1College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China.
Sensors (Basel, Switzerland)
|July 12, 2025
Summary
This study introduces a new method for visual place recognition (VPR) to improve accuracy in changing conditions. The Dynamic Difference and Dual-Path Feature Enhancement (DD-DPFE) method enhances feature discrimination and robustness against noise and appearance drift.
Area of Science:
- Computer Vision
- Robotics
- Artificial Intelligence
Background:
- Visual place recognition (VPR) systems struggle with appearance drift and noise.
- Existing methods lack robustness in dynamic and complex environments.
Purpose of the Study:
- To propose a novel method, DD-DPFE, for enhancing VPR performance.
- To improve robustness against appearance changes and noise interference.
Main Methods:
- Developed a Dynamic Difference and Dual-Path Feature Enhancement (DD-DPFE) method.
- Integrated differential attention and serial-parallel adapters into the DINOv2 model.
- Implemented a two-way feature enhancement module with global and local branches.
Main Results:
- The DD-DPFE method significantly improved performance across various environmental tests.
- Demonstrated superior results in night scene simulations, highlighting enhanced anti-jamming capabilities.
- Validated increased discriminative power and robustness in complex scenes.
Conclusions:
- The proposed DD-DPFE method effectively addresses limitations in VPR systems.
- Achieved enhanced robustness and discriminative power, particularly in challenging conditions like low light.
- DD-DPFE offers a promising solution for reliable visual place recognition.
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