Moving object tracking on panoramic images

P. Földesy, I. Szatmári, A. Zarándy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Analogic CNN algorithms are combined with the special properties of a panoramic imaging device called PAL optics. The resulting system is capable to identify and track moving objects in 360 degrees field of view real-time. Image processing engine was the ALADDIN system with a 64x64 array size CNNUM chip. As the image sensor, we tested the optical input of the CNNUM chip in one experiment, and in other cases, we used a regular camera.

Original languageEnglish
Title of host publicationProceedings of the 7th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA 2002
EditorsRonald Tetzlaff
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages63-70
Number of pages8
ISBN (Electronic)981238121X
DOIs
Publication statusPublished - Jan 1 2002
Event7th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA 2002 - Frankfurt, Germany
Duration: Jul 22 2002Jul 24 2002

Publication series

NameProceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications
Volume2002-January

Other

Other7th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA 2002
CountryGermany
CityFrankfurt
Period7/22/027/24/02

Keywords

  • Cameras
  • Cellular neural networks
  • Engines
  • Image processing
  • Image sensors
  • Optical devices
  • Optical imaging
  • Optical sensors
  • Real time systems
  • Testing

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software
  • Electrical and Electronic Engineering
  • Modelling and Simulation

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  • Cite this

    Földesy, P., Szatmári, I., & Zarándy, A. (2002). Moving object tracking on panoramic images. In R. Tetzlaff (Ed.), Proceedings of the 7th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA 2002 (pp. 63-70). [1035036] (Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications; Vol. 2002-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CNNA.2002.1035036