Decision Fusion for Target Detection Using Multi-spectral Image Sequences from Moving Cameras

  • Luis López-Gutiérrez
  • Leopoldo Altamirano-Robles
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3523)

Abstract

In this paper an approach for automatic target detection and tracking, using multisensor image sequences with the presence of camera motion is presented. The approach consists of three parts. The first part uses a motion segmentation method for the detection of targets in the visible images sequence. The second part uses a Gaussian background model for detecting objects presented in the infrared sequence, which is preprocessed to eliminate the camera motion. The third part combines the individual results of the detection systems; it extends the Joint Probabilistic Data Association (JPDA) algorithm to handle an arbitrary number of sensors. Our approach is tested using image sequences with high clutter on dynamic environments. Experimental results show that the system detects 99% of the targets in the scene, and the fusion module removes 90% of the false detections.

Keywords

Target Detection Camera Motion Motion Segmentation Decision Fusion False Target 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Luis López-Gutiérrez
    • 1
  • Leopoldo Altamirano-Robles
    • 1
  1. 1.National Institute of Astrophysics Optics and ElectronicsPueblaMéxico

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