Search results for "projection"
showing 10 items of 378 documents
Uncalibrated Reconstruction: An Adaptation to Structured Light Vision
2003
Abstract Euclidean reconstruction from two uncalibrated stereoscopic views is achievable from the knowledge of geometrical constraints about the environment. Unfortunately, these constraints may be quite difficult to obtain. In this paper, we propose an approach based on structured lighting, which has the advantage of providing geometrical constraints independent of the scene geometry. Moreover, the use of structured light provides a unique solution to the tricky correspondence problem present in stereovision. The projection matrices are first computed by using a canonical representation, and a projective reconstruction is performed. Then, several constraints are generated from the image an…
Seam-Based Edge Blending for Multi-Projection Systems
2016
Perceptual seamlessness of large-scale tiled displays is still a challenge. One way to avoid Bezel effects from contiguous displays is to blend superimposed parts of the image over the edges. This work proposes a new approach for edge blending. It is based on intensity edge blending adapted on the seam description of the image content. The main advantage of this method is to reduce visual artifacts thanks to context adaptation and smooth transitions. We evaluate the quality of the method with a perceptual experiment where it is compared with state-of-the-art methods. The new method shows most improvement in low frequency areas compared to the other techniques. This method can be inserted in…
Reduction of the number of spectral bands in Landsat images: a comparison of linear and nonlinear methods
2006
We describe some applications of linear and nonlinear pro- jection methods in order to reduce the number of spectral bands in Land- sat multispectral images. The nonlinear method is curvilinear component analysis CCA, and we propose an adapted optimization of it for image processing, based on the use of principal-component analysis PCA, a linear method. The principle of CCA consists in reproducing the topol- ogy of the original space projection points in a reduced subspace, keep- ing the maximum of information. Our conclusions are: CCA is an im- provement for dimension reduction of multispectral images; CCA is really a nonlinear extension of PCA; CCA optimization through PCA called CCAinitP…
Automatic Image Annotation Using Random Projection in a Conceptual Space Induced from Data
2018
The main drawback of a detailed representation of visual content, whatever is its origin, is that significant features are very high dimensional. To keep the problem tractable while preserving the semantic content, a dimen- sionality reduction of the data is needed. We propose the Random Projection techniques to reduce the dimensionality. Even though this technique is sub-optimal with respect to Singular Value Decomposition its much lower computational cost make it more suitable for this problem and in par- ticular when computational resources are limited such as in mobile terminals. In this paper we present the use of a "conceptual" space, automatically induced from data, to perform automa…
Automated detection of patient movement during a CBCT scan based on the projection data.
2015
Objectives To develop an automated procedure to detect patient motion on the projection images acquired during a cone beam computed tomography (CBCT) scan and to evaluate the method's feasibility on small real-world CBCT images in relation to visual assessment. Methods Based on optical flow theory, software was developed using the sequence of the projection images of a CBCT machine for automated detection of patient motion. Averaged acceleration vectors were used as measurement data and compared with visual assessment of the projection images displayed as video. Seventy-nine CBCT data sets (small field-of-view: 40 mm) from our patient database were selected in a sequential fashion and evalu…
PCA Gaussianization for image processing
2009
The estimation of high-dimensional probability density functions (PDFs) is not an easy task for many image processing applications. The linear models assumed by widely used transforms are often quite restrictive to describe the PDF of natural images. In fact, additional non-linear processing is needed to overcome the limitations of the model. On the contrary, the class of techniques collectively known as projection pursuit, which solve the high-dimensional problem by sequential univariate solutions, may be applied to very general PDFs (e.g. iterative Gaussianization procedures). However, the associated computational cost has prevented their extensive use in image processing. In this work, w…
Contribution to variational analysis : stability of tangent and normal cones and convexity of Chebyshev sets
2014
The aim of this thesis is to study the following three problems: 1) We are concerned with the behavior of normal cones and subdifferentials with respect to two types of convergence of sets and functions: Mosco and Attouch-Wets convergences. Our analysis is devoted to proximal, Fréchet, and Mordukhovich limiting normal cones and subdifferentials. The results obtained can be seen as extensions of Attouch theorem to the context of non-convex functions on locally uniformly convex Banach space. 2) For a given bornology β on a Banach space X we are interested in the validity of the following "lim inf" formula (…).Here Tβ(C; x) and Tc(C; x) denote the β-tangent cone and the Clarke tangent cone to …
A product space reformulation with reduced dimension for splitting algorithms
2021
AbstractIn this paper we propose a product space reformulation to transform monotone inclusions described by finitely many operators on a Hilbert space into equivalent two-operator problems. Our approach relies on Pierra’s classical reformulation with a different decomposition, which results in a reduction of the dimension of the outcoming product Hilbert space. We discuss the case of not necessarily convex feasibility and best approximation problems. By applying existing splitting methods to the proposed reformulation we obtain new parallel variants of them with a reduction in the number of variables. The convergence of the new algorithms is straightforwardly derived with no further assump…
Application of alternating projection method to ensure feasibility of shadowing cross-correlation models
2007
A novel procedure based on the alternating projection method to adjust experimental shadowing cross-correlation (SCC) matrices is proposed. Given an SCC matrix derived from any experimental model, this procedure finds the nearest diagonalisable correlation matrix. This adjustment allows a proper simulation of shadowing samples, since it produces correlation matrices for which Cholesky factorisation is feasible. Simulation results using this procedure for three different SCC models are compared and discussed.
Preparation and characterization of brass-based coatings
2018
Cold Spray (CS) has been widely investigated owing to its high deposition efficiency and retention of the properties of starting materials. Thus, this process has shown obvious advantages over the fabrication of different copper-based deposits and its alloys over other techniques, such as electroplating, Laser Cladding or thermal spraying. As one of the main copper alloys, brass is implanted in the fields of architecture or industry. Nevertheless, nowadays it is clear that there is very little work on brass coatings, and they were mainly made by electroplating and any other deposition methods, which has severely limits their uses in many applications.This study was applied to develop the br…