Book ChapterDOI
Optical-Flow Estimation while Preserving Its Discontinuities: A Variational Approach
Rachid Deriche,Pierre Kornprobst,Gilles Aubert +2 more
- pp 71-80
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TLDR
This paper describes a variational approach devised for the purpose of estimating optical flow from a sequence of images with the constraint to preserve the flow discontinuities, set as a regularization and minimization of a non quadratic functional.Abstract:
This paper describes a variational approach devised for the purpose of estimating optical flow from a sequence of images with the constraint to preserve the flow discontinuities. This problem is set as a regularization and minimization of a non quadratic functional. The Tikhonov quadratic regularization term usually used to recover smooth solution is replaced by a particular function of the gradient flow specifically derived to allow flow discontinuities formation in the solution. Conditions to be fulfilled by this specific regularizing term, to preserve discontinuities and insure stability of the regularization problem, are also derived. To minimize this non quadratic functional, two different methods have been investigated. The first one is an iterative scheme to solve the associated non-linear Euler-Lagrange equations. The second solution introduces dual variables so that the minimization problem becomes a quadratic or a convex functional minimization problem. Promising experimental results on synthetic and real image sequences will illustrate the capabilities of this approach.read more
Citations
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Book ChapterDOI
High Accuracy Optical Flow Estimation Based on a Theory for Warping
TL;DR: By proving that this scheme implements a coarse-to-fine warping strategy, this work gives a theoretical foundation for warping which has been used on a mainly experimental basis so far and demonstrates its excellent robustness under noise.
Book
Anisotropic diffusion in image processing
TL;DR: This work states that all scale-spaces fulllling a few fairly natural axioms are governed by parabolic PDEs with the original image as initial condition, which means that, if one image is brighter than another, then this order is preserved during the entire scale-space evolution.
Proceedings Article
Robot vision
TL;DR: A scheme is developed for classifying the types of motion perceived by a humanlike robot and equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented.
Book ChapterDOI
A Review of Nonlinear Diffusion Filtering
TL;DR: An overview of scale-space and image enhancement techniques which are based on parabolic partial differential equations in divergence form and how this filter class allows to integrate a-priori knowledge into the evolution.
Journal ArticleDOI
Variational Methods for Multimodal Image Matching
TL;DR: The thrust of this paper is that many of the existing methods for nonrigid monomodal registration that use simple criteria for comparing the intensities can be extended to the multimodal case where more complex intensity similarity measures are necessary.
References
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Journal ArticleDOI
Nonlinear total variation based noise removal algorithms
TL;DR: In this article, a constrained optimization type of numerical algorithm for removing noise from images is presented, where the total variation of the image is minimized subject to constraints involving the statistics of the noise.
Journal ArticleDOI
Determining optical flow
TL;DR: In this paper, a method for finding the optical flow pattern is presented which assumes that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image, and an iterative implementation is shown which successfully computes the Optical Flow for a number of synthetic image sequences.
Proceedings ArticleDOI
Determining Optical Flow
TL;DR: In this article, a method for finding the optical flow pattern is presented which assumes that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image, and an iterative implementation is shown which successfully computes the Optical Flow for a number of synthetic image sequences.
Journal ArticleDOI
Performance of optical flow techniques
TL;DR: These comparisons are primarily empirical, and concentrate on the accuracy, reliability, and density of the velocity measurements; they show that performance can differ significantly among the techniques the authors implemented.