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ACIVS
2015
Springer

Fast and Robust Variational Optical Flow for High-Resolution Images Using SLIC Superpixels

3 years 3 months ago
Fast and Robust Variational Optical Flow for High-Resolution Images Using SLIC Superpixels
We show how pixel-based methods can be applied to a sparse image representation resulting from a superpixel segmentation. On this sparse image representation we only estimate a single motion vector per superpixel, without working on the full-resolution image. This allows the accelerated processing of high-resolution content with existing methods. The use of superpixels in optical flow estimation was studied before, but existing methods typically estimate a dense optical flow field – one motion vector per pixel – using the full-resolution input, which can be slow. Our novel approach offers important speed-ups compared to dense pixel-based methods, without significant loss of accuracy.
Simon Donné, Jan Aelterman, Bart Goossens,
Added 13 Apr 2016
Updated 13 Apr 2016
Type Journal
Year 2015
Where ACIVS
Authors Simon Donné, Jan Aelterman, Bart Goossens, Wilfried Philips
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