An Implementation of Combined Local-Global Optical Flow
Jorge Jara-Wilde, Mauricio Cerda, José Delpiano, Steffen Härtel
→ BibTeX
    title   = {{An Implementation of Combined Local-Global Optical Flow}},
    author  = {Jara-Wilde, Jorge and Cerda, Mauricio and Delpiano, José and Härtel, Steffen},
    journal = {{Image Processing On Line}},
    volume  = {5},
    pages   = {139--158},
    year    = {2015},
    doi     = {10.5201/ipol.2015.44},
% if your bibliography style doesn't support doi fields:
    note    = {\url{}}
Jorge Jara-Wilde, Mauricio Cerda, José Delpiano, and Steffen Härtel, An Implementation of Combined Local-Global Optical Flow, Image Processing On Line, 5 (2015), pp. 139–158.

Communicated by Enric Meinhardt-Llopis
Demo edited by Enric Meinhardt-Llopis


Optical Flow (OF) approaches for motion estimation calculate vector fields for the apparent velocities of objects in image sequences. In 1981 Horn and Schunck (HS) introduced two basic assumptions: 'brightness value constancy' and 'smooth variation' to estimate a smooth OF field over the entire image -global approach-. In parallel, Lucas and Kanade (LK) assumed constant motion patterns for image patches, estimating piecewise-homogeneous OF fields -local approach-. Several variations of these approaches exist today. Here we present the combined local-global (CLG) approach by Bruhn et al. which encompasses properties of HS-OF and LK-OF, aiming to improve the OF accuracy for small-scale variations, while delivering the HS-OF dense and smooth fields. A multiscale implementation is provided for 2D images, together with two numerical solvers: Successive Over-Relaxation and the faster Pointwise-Coupled Gauss-Seidel by Bruhn et al.. The algorithm works on gray-scale (single channel) images, with color images being converted prior to the OF computation.


Non-Reviewed Supplementary Materials

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