Multiple vehicles detection and tracking for intelligent transport systems using machine learning approaches

  • Ngoc Dung Bui

    University of Transport and Communications, No 3 Cau Giay Street, Hanoi, Vietnam.
  • Dzung Lai Manh

    University of Transport and Communications, No 3 Cau Giay Street, Hanoi, Vietnam.
  • Vu Hieu Tran

    University of Transport and Communications, No 3 Cau Giay Street, Hanoi, Vietnam.
  • Binh T. H. Nguyen

    Ho Chi Minh City University of Technology, HCM City, Vietnam.
Từ khóa: Vehicle detection, tracking, background subtraction, optical flow, Kalman filters

Tóm tắt

Video surveillance is emerging research field of intelligent transport systems. This paper presents some techniques which use machine learning and computer vision in vehicles detection and tracking. Firstly the machine learning approaches using Haar-like features and Ada-Boost algorithm for vehicle detection are presented. Secondly approaches to detect vehicles using the background subtraction method based on Gaussian Mixture Model and to track vehicles using optical flow and multiple Kalman filters were given. The method takes advantages of distinguish and tracking multiple vehicles individually. The experimental results demonstrate high accurately of the method.

Tài liệu tham khảo

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