Earticle

초록

영어

In this study, we address the problem of multi-person detection and tracking in challenging scenes using sparse stereo information. In each frame, only a sparse set of object feature points are extracted. All these feature points are then projected onto a plan-view map, and grouped into several clusters by employing the biometric information, the optical flow information of object feature points, as well as the width of a person. By producing clusters, the location of a possible person can be determined. In addition, a Modified Joint Probabilistic Data Association Filter (MJPDAF) is proposed for improving the performance of measurements association during the people tracking process. Compared to the traditional JPDAF, the methods for the construction of the validation matrix and the calculation of association probabilities are improved. Experiments on challenging datasets demonstrate that the proposed algorithm is robust for people detection and tracking through fixed stereo vision.

목차

Abstract
 1. Introduction
  1.1 Proposed Contribution
 2. System Overview
 3. Preliminaries
  3.1. Sparse 3D Feature Calculation
  3.2. Making a Plan-view Map
 4. People Detection
  4.1 Bin based Clustering
  4.2 Clustering using Biometric Information
  4.3 Clustering by Optical Flow and Person Width
  4.4 Clustering by Optical Flow
  4.5 Clustering by Person Width
  4.6 People Localization
 5. People Tracking
 6. Experiments
  6.1 Setting Parameters
  6.2 Experimental Results
 7. Conclusions
 Acknowledgements
 References

키워드

저자

• Keli Hu [ Department of Computer Science and Engineering, Shaoxing University, Shaoxing 312000, Zhejiang, China ]
• Yuzhang Gu [ Key Laboratory of Wireless Sensor Network & Communication, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China ]
• Shigen Shen [ Department of Computer Science and Engineering, Shaoxing University, Shaoxing 312000, Zhejiang, China ]
• Cheng Zhang [ Key Laboratory of Wireless Sensor Network & Communication, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China ]
• Yunlong Zhan [ Key Laboratory of Wireless Sensor Network & Communication, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China ]

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