An Implementation of Combined Local-Global Optical Flow
Jorge Jara-Wilde, Mauricio Cerda, José Delpiano, Steffen Härtel
→ BibTeX
@article{ipol.2015.44,
    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{https://doi.org/10.5201/ipol.2015.44}}
published
2015-06-25
reference
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. https://doi.org/10.5201/ipol.2015.44

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

Abstract

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.

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