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A Trinocular System for Pedestrian Localization by Combining Template Matching with Geometric Constraint
Jinjing Zhao1, Sen Huang1, Yancheng Li1
1School of Electronics, Peking University, Beijing 100871, China.
Sensors (Basel, Switzerland)
|October 16, 2025
Summary
This study introduces a novel trinocular stereo vision system for accurate pedestrian localization. The framework enhances depth estimation and achieves real-time performance, outperforming existing binocular methods.
Area of Science:
- Computer Vision
- Robotics
- Sensor Fusion
Background:
- Pedestrian localization is crucial for intelligent outdoor systems.
- Conventional binocular stereo vision methods face limitations in accuracy and efficiency.
- Advanced sensing is required for reliable outdoor navigation and safety.
Purpose of the Study:
- To develop an improved pedestrian localization system using trinocular stereo vision.
- To enhance depth estimation accuracy and processing efficiency compared to binocular approaches.
- To enable real-time pedestrian detection and tracking in outdoor environments.
Main Methods:
- A trinocular camera configuration in an equilateral triangle setup for complementary perspectives.
- Integration of multi-scale template matching for initial depth estimation.
- Enforcement of three-view geometric consistency for refined depth estimates.
- Combination with YOLOv8-s detector for object detection and localization.
Main Results:
- Achieved a mean absolute error of 0.435 m for pedestrian depth estimation.
- Demonstrated an average processing time of 3.13 ms per target, surpassing binocular methods.
- Real-time operation at >30 Hz with end-to-end latency of ~32.56 ms for up to nine pedestrians.
Conclusions:
- The proposed trinocular stereo vision framework significantly improves pedestrian localization accuracy and efficiency.
- The system offers a robust solution for real-time outdoor intelligent systems.
- This approach provides a foundation for enhanced autonomous navigation and safety systems.
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