Search results for "Specularity"

P2D: a self-supervised method for depth estimation from polarimetry

2021

Monocular depth estimation is a recurring subject in the field of computer vision. Its ability to describe scenes via a depth map while reducing the constraints related to the formulation of perspective geometry tends to favor its use. However, despite the constant improvement of algorithms, most methods exploit only colorimetric information. Consequently, robustness to events to which the modality is not sensitive to, like specularity or transparency, is neglected. In response to this phenomenon, we propose using polarimetry as an input for a self-supervised monodepth network. Therefore, we propose exploiting polarization cues to encourage accurate reconstruction of scenes. Furthermore, we…

2020

This work introduces a method to estimate reflectance, shading, and specularity from a single image. Reflectance, shading, and specularity are intrinsic images derived from the dichromatic model. Estimation of these intrinsic images has many applications in computer vision such as shape recovery, specularity removal, segmentation, or classification. The proposed method allows for recovering the dichromatic model parameters thanks to two independent quadratic programming steps. Compared to the state of the art in this domain, our approach has the advantage to address a complex inverse problem into two parallelizable optimization steps that are easy to solve and do not require learning. The p…

Estimating intrinsic image from successive images by solving underdetermined and overdetermined systems of the dichromatic model

2020

International audience; Estimating an intrinsic image from a sequence of successive images taken from an object at different angles of illumination can be used in various applications such as objects recognition, color classification, and the like; because, in so doing, it can provide more visual information. Meanwhile, according to the well-known dichromatic model, each image can be considered a linear combination of three components, including intrinsic image, shading factor, and specularity. In this study, at first, two simple independent constrained and parallelized quadratic programming steps were used for computing values of the shading factor and the specularity of each successive of…

A 3D Scanner for Transparent Glass

2009

Many practical tasks in industry, such as automatic inspection or robot vision, often require the scanning of three-dimensional shapes by use of non-contact techniques. However, few methods have been proposed to measure three-dimensional shapes of transparent objects because of the difficulty of dealing with transparency and specularity of the surface. This paper presents a 3D scanner for transparent glass objects based on Scanning From Heating (SFH), a new method that makes use of local surface heating and thermal imaging.

Scanning from heating: 3D shape estimation of transparent objects from local surface heating.

2009

Today, with quality becoming increasingly important, each product requires three-dimensional in-line quality control. On the other hand, the 3D reconstruction of transparent objects is a very difficult problem in computer vision due to transparency and specularity of the surface. This paper proposes a new method, called Scanning From Heating (SFH), to determine the surface shape of transparent objects using laser surface heating and thermal imaging. Furthermore, the application to transparent glass is discussed and results on different surface shapes are presented.

Quadratic Objective Functions for Dichromatic Model Parameters Estimation

2017

International audience; In this paper, we present a novel method to estimate dichromatic model parameters from a single color image. Estimation of reflectance, shading and specularity has many applications such as shape recovery, specularity removal and facilitates classical image processing and computer vision tasks such as segmentation or classification. Our method is based on two successive and independent constrained quadratic programming steps to recover the parameters of the model. Compared to recent methods, our approach has the advantage to transform a complex inverse problem into two parralelizable optimization steps that are much easier to solve. We have compared our method with r…