Earticle

초록

영어

This paper presents a robust and efficient method for vehicle detection in dynamic traffic environments. First, two adaptive vehicle hypothesis generation methods based on shadow and vehicle wave are presented, and then we assemble these two features into vehicle hypothesis. A hypothesis verification algorithm based on vehicle motion trajectory is proposed, the on-line hypothesis verification algorithm based on vehicle motion trajectory can not only reduce the false positive alarm caused by interferences, but also handle the problem that the classifiers generated in the off-line training phase is closely related to the diversity of positive and negative samples. Quantitative analysis on both public vehicle image datasets and real-time video presents a result of 85.58% detection rate with 4.13% false positive rate. And our algorithm could run as fast as 40ms/frame on PC platform.

목차

Abstract
 1. Introduction
 2. Detection by Knowledge-based Features
  2.1. Detection based on Shadow
  2.2. Detection Based on Vehicle Wave
  2.3. Knowledge-based Features Fusion
 3. Verification by Motion Trajectory
  3.1. Definition of Object
  3.2. HV Algorithm based on Motion Trajectory
 5. Experiments
  5.1. Experimental Datasets and Performance Metrics
  5.2. Main Parameter Settings
  5.3. Results and Comparisons
 6. Conclusions
 Acknowledgements
 References

키워드

저자

• Wenhui Li [ College of Computer Science and Technology， Jilin University, State Key Laboratory of Automotive Simulation and Control, Jilin University ]
• Peixun Liu [ College of Computer Science and Technology， Jilin University, State Key Laboratory of Automotive Simulation and Control, Jilin University ]
• Ying Wang [ College of Computer Science and Technology， Jilin University, State Key Laboratory of Automotive Simulation and Control, Jilin University ]
• Hongyin Ni [ College of Computer Science and Technology， Jilin University, State Key Laboratory of Automotive Simulation and Control, Jilin University ]
• Chao Wen [ College of Computer Science and Technology， Jilin University, State Key Laboratory of Automotive Simulation and Control, Jilin University ]
• Jiahao Fan [ College of Computer Science and Technology， Jilin University, State Key Laboratory of Automotive Simulation and Control, Jilin University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605