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논문검색

Improved Multi-target Tracking Algorithm Based on Gaussian Mixture Particle PHD Filter

원문정보

Qing Lin, Pei Cao, Dingan Liao, Yongzhao Zhan, Yaping Yang

보안공학연구지원센터(IJMUE) International Journal of Multimedia and Ubiquitous Engineering Vol.10 No.2 2015.02 pp.227-236
피인용수 : 0건 (자료제공 : 네이버학술정보)

초록

영어

The paper proposes Gaussian mixture particle probability hypothesis density filter(PHD) algorithm ,which can effectively solve the problem that the object number is changing or unknown, based on particle PHD filter. This algorithm calculates the object number and state by recursive procedure, avoiding the uncertainty of target state estimation caused by particle sampling and clustering. Gaussian mixture particle is introduced to effectively maintain the multi-modal distribution of each target，reducing the complexity of calculation.

목차

Abstract
 1. Introduction
 2. Hybrid Particle Filter
 3. PHD Filter
 4. Gaussian Mixture PHD Particle Filter Algorithm
 5. Experiment Result
 6. Conclusion
 References

키워드

저자정보

  • Qing Lin School of Computer Science and Telecommunication Engineering, Jiangsu University, Zhenjiang Jiangsu, 212013, School of Computer Science and Technology, Nanjing University and Technology, Nanjing Jiangsu
  • Pei Cao School of Computer Science and Telecommunication Engineering, Jiangsu University, Zhenjiang Jiangsu, 212013
  • Dingan Liao School of Computer Science and Telecommunication Engineering, Jiangsu University, Zhenjiang Jiangsu, 212013, Changzhou Textile Garment Institute Changzhou Jiangsu, 213164
  • Yongzhao Zhan School of Computer Science and Telecommunication Engineering, Jiangsu University, Zhenjiang Jiangsu, 212013
  • Yaping Yang School of Computer Science and Telecommunication Engineering, Jiangsu University, Zhenjiang Jiangsu, 212013

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