Reliable Estimation of Dense Optical Flow Fields with Large Displacements
By Luis Álvarez, Joachim Weickert, Javier Sánchez Pérez. International Journal of Computer Vision, 2000
362 citations recorded by the source corpus.
Subfields: Biophysics, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/8e06ea3d5c3047aa41eebd2b6e2d265c4b87e057
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biophysics
- Jitendra Malik
- Thomas Brox
- Christoph Schnörr
- Eirikur Agustsson
- Jean-Philippe Pons
- Renaud Keriven
- Olivier D. Faugeras
- Johannes Ballé
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Jitendra Malik
- Andrew Zisserman
- Cordelia Schmid
- Dacheng Tao
- Ming-Hsuan Yang
- Trevor Darrell
- Thomas Brox
Citations in the corpus
- High Accuracy Optical Flow Estimation Based on a Theory for Warping (2004, methodology): “models [19, 2] have been used to tackle large displacements.”
- A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion (2001, methodology): “early anisotropic modification of the Horn and Schunck functional is due to Nagel (1983), see also Alvarez et al. (2000), Enkelmann (1988), Nagel (1987), Nagel and Enkelmann (1986), Schnörr (1991, 1993), and Snyder (1991).”
- Ieee Transactions on Pattern Analysis and Machine Intelligence 1 Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation (2011, positive): “Finally, when not linearizing the constancy constraints, the model can deal with large displacements [1].”
- Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint (2001, background): “[ 2 ]. Evidently, the single Eq. (1) is not sufficient to determine the two unknown functions u and v uniquely (aperture problem).”
- Scale-Space Flow for End-to-End Optimized Video Compression (2020, background): “[6, 18, 13]) as well as the use of multi-scale pyramids in deep flow estimation networks [28, 14].”
- Modelling dynamic scenes by registering multi-view image sequences (2005, methodology): “Basically, it consists in applying the algorithm to a set of smoothed and subsampled images [1].”
- Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow (2014, neutral): “The classical coarse-to-fine framework for large displacement motions that is used by most optical flow algorithms was originally formulated in [1].”