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Cross-Video Pedestrian Tracking Algorithm with a Coordinate Constraint.

Cheng Huang1,2, Weihong Li1,2,3, Guang Yang1,2,3

  • 1School of Geography, South China Normal University, Guangzhou 510631, China.

Sensors (Basel, Switzerland)
|February 10, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new cross-video pedestrian tracking method using spatial information to improve accuracy and robustness. The enhanced algorithm boosts successful pedestrian matching and continuous tracking in surveillance systems.

Keywords:
coordinate featurescross-videooverlapping viewpedestrian tracking

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Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Surveillance Technology

Background:

  • Pedestrian tracking in surveillance videos is essential for personnel management but limited by single video coverage.
  • Current cross-video tracking methods often fail due to reliance on appearance features, leading to low accuracy and robustness.

Purpose of the Study:

  • To develop an improved cross-video pedestrian tracking algorithm.
  • To enhance the accuracy and robustness of continuous pedestrian tracking across multiple surveillance videos.

Main Methods:

  • The proposed algorithm integrates spatial information, including pedestrian coordinate features from different videos.
  • A linear weighting strategy is employed, focusing on the overlapping views during the tracking process.

Main Results:

  • The new method significantly improves the success rate of target pedestrian matching compared to traditional approaches.
  • Enhanced robustness in continuous pedestrian tracking is achieved, outperforming existing techniques.

Conclusions:

  • The developed algorithm offers a viable solution for accurate and robust cross-video pedestrian tracking.
  • This research provides a valuable reference for pedestrian tracking and crowd management applications in video surveillance.