DI-UMONS : Dépôt institutionnel de l’université de Mons

Recherche transversale
(titres de publication, de périodique et noms de colloque inclus)
2014-03-25 - Article/Dans un journal avec peer-review - Anglais - 12 page(s)

Mahmoudi Sidi , Kierzynka Michal, Manneback Pierre , Kurowski Krzysztof, "Real-time motion tracking using optical flow on multiple GPUs" in Bulletin of the Polish Academy of Sciences. Technical Sciences, 62, 1, 139-150, 10.2478/bpasts-2014-0016

  • Edition : Polska Akademia Nauk (Poland)
  • Codes CREF : Techniques d'imagerie et traitement d'images (DI2770), Technologie informatique hardware (DI2560), Informatique appliquée logiciel (DI2570), Informatique générale (DI1162)
  • Unités de recherche UMONS : Informatique, Logiciel et Intelligence artificielle (F114)
  • Instituts UMONS : Institut de Recherche en Technologies de l’Information et Sciences de l’Informatique (InforTech), Institut NUMEDIART pour les Technologies des Arts Numériques (Numédiart)
  • Centres UMONS : Centre de Recherche en Technologie de l’Information (CRTI)

Abstract(s) :

(Anglais) Motion tracking algorithms are widely used in computer vision related research. However, the new video standards, especially those in high resolutions, cause that current implementations, even running on modern hardware, no longer meet the needs of real-time processing. To overcome this challenge several GPU (Graphics Processing Unit) computing approaches have recently been proposed. Although they present a great potential of a GPU platform, hardly any is able to process high definition video sequences efficiently. Thus, a need arose to develop a tool being able to address the outlined problem. In this paper we present software that implements optical flow motion tracking using the Lucas-Kanade algorithm. It is also integrated with the Harris corner detector and therefore the algorithm may perform sparse tracking, that is tracking of the meaningful pixels only. This allows to substantially lower the computational burden of the method. Moreover, both parts of the algorithm, i.e. corners selection and tracking, are implemented on GPU and, as a result, the software is immensely fast, allowing for real-time motion tracking on videos in Full HD or even 4K format. In order to deliver the highest performance, it also supports multiple GPUs systems, where it scales up very well.

Identifiants :
  • DOI : 10.2478/bpasts-2014-0016