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Pedestrian Tracking-by-Detection Using Image Density Projections and Particle Filters

  • B. Lacabex
  • A. Cuesta-Infante
  • A. S. Montemayor
  • J. J. Pantrigo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9108)

Abstract

Video-based people detection and tracking is an important task for a wide variety of applications concerning computer vision systems. In this work, we propose a pedestrian tracking-by-detection system focused on the role of computational performance. To this aim, we have developed a computationally efficient method for people detection, based on background subtraction and image density projections. Tracking is performed by a set of trackers based on particle filters that are properly associated with detections. We test our system on different well-known benchmark datasets. Experimental results reveal that the proposed method is efficient and effective. Specifically, it obtains a processing rate of 22 frames per second on average when tracking a maximum number of 9 people.

Keywords

People detection People tracking Tracking-by-detection Image density projections Particle filters 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • B. Lacabex
    • 1
  • A. Cuesta-Infante
    • 1
  • A. S. Montemayor
    • 1
  • J. J. Pantrigo
    • 1
  1. 1.Departamento de Ciencias de la ComputaciónUniversidad Rey Juan CarlosMadriaSpain

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