Paper Title:
An New Method for Multi-Object Tracking Using Energy Minimization-Based Data Association
  Abstract

multiple object tracking is an active and important research topic. It faces many challenging problems. Object extraction and data association are two most key steps in multiple object tracking. To improve tracking performance, this paper proposed a tracking method which combines Kalman filter and energy minimization-based data association. Moving objects are segmented through frame difference. Its can be consider as the vertex. All detections in adjacent frames are be used to construct a graph. The energy is finally minimized with a graph cuts optimization. Data association can be consider as multiple labeling problems. Object corresponding can be obtained through energy minimization. Experiment results demonstrate this method can be accurately tracking two moving objects.

  Info
Periodical
Chapter
Chapter 3: Signal and Data Processing, Data Mining, Applied and Computational Mathematics
Edited by
B. L. Liu, Minghai Yuan, Guorong Chen and Jun Peng
Pages
1822-1825
DOI
10.4028/www.scientific.net/AMM.427-429.1822
Citation
Z. H. Wang, K. C. Hong, "An New Method for Multi-Object Tracking Using Energy Minimization-Based Data Association", Applied Mechanics and Materials, Vols. 427-429, pp. 1822-1825, Sep. 2013
Online since
September 2013
Price
US$ 28,-
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