Mar 10, 2009 · We present a new method for addressing robust depth estimation from a stereo pair under varying illumination conditions.
A convex energy function that takes into account the illumination variation model is then derived and minimized subject to various convex constraints arising ...
Oct 22, 2024 · We present a new method for addressing robust depth estimation from a stereo pair under varying illumination conditions. First, a spatially ...
A spatially varying multiplicative model is developed to account for brightness changes induced between left and right views and the resulting ...
We present a new method for addressing robust depth estimation from a stereo pair under varying illumination conditions. First, a spatially varying ...
We present a new method for addressing robust depth estimation from a stereo pair under varying illumination conditions. First, a spatially varying ...
A Convex Optimization Approach for Depth Estimation Under Illumination Variation Wided Miled, Student Member, IEEE, Jean-Christophe Pesquet, Senior Member, ...
People also ask
What is convex optimization in deep learning?
What is a convex optimization model?
What are the methods for solving convex optimization problems?
What is an example of convex optimization?
We present a new method for addressing robust depth estimation from a stereo pair under varying illumination conditions.
In this paper, we suggest a novel statistic-based method for estimating single and multiple illuminants using convex functions.
Missing: Depth | Show results with:Depth
We propose a convex approach to address the problem of dense disparity estimation under varying illumination conditions. A convex energy function is derived ...