Journal of Real-Time Image Processing

, Volume 11, Issue 4, pp 713–730 | Cite as

Massively parallel Lucas Kanade optical flow for real-time video processing applications

  • Aurélien PlyerEmail author
  • Guy Le Besnerais
  • Frédéric Champagnat
Special Issue Paper


This paper deals with dense optical flow estimation from the perspective of the trade-off between quality of the estimated flow and computational cost which is required by real-world applications. We propose a fast and robust local method, denoted by eFOLKI, and describe its implementation on GPU. It leads to very high performance even on large image formats such as 4 K (3,840 × 2,160) resolution. In order to assess the interest of eFOLKI, we first present a comparative study with currently available GPU codes, including local and global methods, on a large set of data with ground truth. eFOLKI appears significantly faster while providing quite accurate and highly robust estimated flows. We then show, on four real-time video processing applications based on optical flow, that eFOLKI reaches the requirements both in terms of estimated flows quality and of processing rate.


Optical flow Motion GPU Super-resolution Dense 



The authors are most grateful to Benjamin Leclaire and Yves Le Sant at ONERA/DAFE for years of fruitful collaboration.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Aurélien Plyer
    • 1
    Email author
  • Guy Le Besnerais
    • 1
  • Frédéric Champagnat
    • 1
  1. 1.ONERAPalaiseauFrance

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