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Motion Detection by Microcontroller for Panning Cameras

  • Jesús Benito-PicazoEmail author
  • Ezequiel López-Rubio
  • Juan Miguel Ortiz-de-Lazcano-Lobato
  • Enrique Domínguez
  • Esteban J. Palomo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10338)

Abstract

Motion detection is the first essential process in the extraction of information regarding moving objects. The approaches based on background difference are the most used with fixed cameras to perform motion detection, because of the high quality of the achieved segmentation. However, real time requirements and high costs prevent most of the algorithms proposed in literature to exploit the background difference with panning cameras in real world applications. This paper presents a new algorithm to detect moving objects within a scene acquired by panning cameras. The algorithm for motion detection is implemented on a Raspberry Pi microcontroller, which enables the design and implementation of a low-cost monitoring system.

Keywords

Foreground detection Background modeling Probabilistic self-organizing maps Background features 

Notes

Acknowledgments

This work is partially supported by the Ministry of Economy and Competitiveness of Spain under grant TIN2014-53465-R, project name Video surveillance by active search of anomalous events. It is also partially supported by the Autonomous Government of Andalusia (Spain) under projects TIC-6213, project name Development of Self-Organizing Neural Networks for Information Technologies; and TIC-657, project name Self-organizing systems and robust estimators for video surveillance. Finally, it is partially supported by the Autonomous Government of Extremadura (Spain) under the project IB13113. All of them include funds from the European Regional Development Fund (ERDF). The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the SCBI (Supercomputing and Bioinformatics) center of the University of Málaga. They also gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan X GPU used for this research.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jesús Benito-Picazo
    • 1
    Email author
  • Ezequiel López-Rubio
    • 1
  • Juan Miguel Ortiz-de-Lazcano-Lobato
    • 1
  • Enrique Domínguez
    • 1
  • Esteban J. Palomo
    • 1
    • 2
  1. 1.Department of Computer Languages and Computer ScienceUniversity of MálagaMálagaSpain
  2. 2.School of Mathematical Sciences and Information TechnologyUniversity of Yachay TechSan Miguel de UrcuquíEcuador

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