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Proceedings ArticleDOI

High-order regularization for stereo color editing

TLDR
This paper pioneers a method for local color editing on stereo image pairs by introducing recent advances in the field of image segmentation, thus allowing a user's edits in one view to be simultaneously performed in the other view.
Abstract
This paper pioneers a method for local color editing on stereo image pairs. We generalize the conventional edit propagation framework to stereo views by introducing recent advances in the field of image segmentation, thus allowing a user's edits in one view to be simultaneously performed in the other view. This new formulation maintains consistent editing quality in both views and avoids singularities by solving a well regularized linear system for edit propagation.

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Citations
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Patent

Device and method for editing a virtual reality scene represented in a curved shape form

TL;DR: In this article, a virtual reality scene (21) represented in a curved shape form is edited by extracting (11A, 11B) planar key views (24A, 24B), obtaining (13, 14) edited versions (27A, 27B) of those key views having respective edits, and propagating (15A, 15B) those edits to at least part of the VR scene.
References
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Book

Iterative Methods for Sparse Linear Systems

Yousef Saad
TL;DR: This chapter discusses methods related to the normal equations of linear algebra, and some of the techniques used in this chapter were derived from previous chapters of this book.
Journal ArticleDOI

Mean shift: a robust approach toward feature space analysis

TL;DR: It is proved the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density.
Journal ArticleDOI

Learning to Detect a Salient Object

TL;DR: A set of novel features, including multiscale contrast, center-surround histogram, and color spatial distribution, are proposed to describe a salient object locally, regionally, and globally.
Journal ArticleDOI

A Closed-Form Solution to Natural Image Matting

TL;DR: A closed-form solution to natural image matting that allows us to find the globally optimal alpha matte by solving a sparse linear system of equations and predicts the properties of the solution by analyzing the eigenvectors of a sparse matrix, closely related to matrices used in spectral image segmentation algorithms.
Journal ArticleDOI

Colorization using optimization

TL;DR: This paper presents a simple colorization method that requires neither precise image segmentation, nor accurate region tracking, and demonstrates that high quality colorizations of stills and movie clips may be obtained from a relatively modest amount of user input.
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