Cicero Mota

Cicero Mota
Federal University of Amazonas | UFAM · Department of Mathematics

Doutor em Ciências (D. Sc.)

About

36
Publications
3,104
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
430
Citations

Publications

Publications (36)
Article
The effect of the hydrostatic pressures on the thermoelectrical properties of SnSe in the Pnma phase is studied using the density functional theory (DFT). The Seebeck coefficient, the electrical conductivity, the electronic and lattice thermal conductivities, the power factor and the figure of merit are investigated. For zero pressure the calculati...
Article
Full-text available
We report theoretical analysis of charge transport process through a single glycine molecule utilizing graphene nanogaps. Density functional theory and non-equilibrium Green’s function method are employed to investigate the transport properties of glycine inside the gap. The projected density of states, transmittance, and the current–voltage charac...
Article
In this work we use ab initio density functional theory (DFT) and propose three new configurations of substituted graphene monolayers where the carbon atoms are replaced selectively by boron and nitrogen. The stable equilibrium geometries and corresponding structural, electronic and transport properties of the resulting graphene-like BC, NC and BN...
Article
The pressure-induced phase transitions in SnSe have been investigated using the first-principles density functional calculations. The experimental results in the nanostructured SnSe revealed a phase transition at 4 GPa whereas that in the well-crystallized samples showed at 10 GPa. To understand the above discrepancy, we have used a pseudohybrid Hu...
Article
Full-text available
Curved image features like corners are good features to track and also the only image regions where motion can be estimated reliably. In addition, such features contain higher amounts of information than straight edges and uniform regions (7, 2). Here we extend previous results related to the uniqueness of curvature features (2) and proof that curv...
Article
Based on the principle of efficient coding, we present a theoretical framework for how to categorize the basic types of changes that can occur in a spatio-temporal signal. First, theoretical results for the problem of estimating multiple transparent motions are reviewed. Then, confidence measures for the presence of multiple motions are used to der...
Article
In every infinite-dimensional vector space we build a complete, non-locally convex linear Hausdorff topology under the prescribed condition that it shall be compatible with a bounded algebraic structure for the space, that is, it admits a bounded Hamel basis whose coefficient linear functionals are continuous. As a byproduct, we obtain the existenc...
Article
Full-text available
Motion selec@5Rj4 is a key feature of visual procPU8Lj However, most models of motion perco tion and motion-selecU neuronscjL8@ acU8R for multiple motions. This is partly becL@5 the theoretico problems related to multiple motions have not been solved, although usefulcefuljU like 'nulling filters' and 'layers' have beenintroducj...
Chapter
Full-text available
We consider the general task of accurately detecting and quantifying orientations in n-dimensional signals s. The main emphasis will be placed on the estimation of motion, which can be thought of as orientation in spatiotemporal signals. Associated problems such as the optimization of matched kernels for deriving isotropic and highly accurate gradi...
Article
Full-text available
Estimation of local orientation in images may be posed as the problem of finding the minimum gray-level variance axis in a local neighborhood. In bivariate images, the solution is given by the eigenvector corresponding to the smaller eigenvalue of a 2 x 2 tensor. For an ideal single orientation, the tensor is rank-deficient, i.e., the smaller eigen...
Conference Paper
Full-text available
The estimation of multiple orientations in multidimensional signals is a strongly non-linear problem to which a two-step solution is here presented. First, the problem is linearized by introducing the so-called mixed-orientation parameters as a unique, albeit implicit, descriptor of the orientations. Second, the non-linearities are decomposed such...
Conference Paper
Full-text available
The incremental Badoiu-Clarkson algorithm finds the smallest ball enclosing n points in d dimensions with at least O(1/radict) precision, after t iteration steps. The extremely simple incremental step of the algorithm makes it very attractive both for theoreticians and practitioners. A simplified proof for this convergence is given. This proof allo...
Article
We present a spatio-temporal analysis of motion at occluding boundaries. The main result is an analytical description of the motions and the distortions that occur at the occluding boundary. Based on this result we analyze occluding motions in the Fourier domain and show that the distortion term has an hyperbolic decay independent of the shape of t...
Article
Full-text available
The paper deals with the estimation of complex motion pat-terns. The complexity is due to (i) the motions of two trans-parent layers, and (ii) an additional change of brightness in the layers, which can be due to an additive source term, an exponential decay, or diffusion. We present new models and constraints for such complex motion patterns. Expe...
Conference Paper
Full-text available
We present a solution to the general problem of estimating multiple orientations in multidimensional signals. The solution is divided in a linear part that provides the mixed-orientation space (MOS) and a nonlinear part that gives the actual orientation spaces. We show that the angle between two overlaid orientations is an invariant that can be der...
Conference Paper
Full-text available
Features like junctions and corners are a rich source of information for image understanding. We present a novel theoretical framework for the analysis of such 2D features in scalar and multispectral images. We model the features as occluding superpositions of two different orientations and derive a new constraint equation based on the tensor produ...
Conference Paper
Full-text available
Local orientation estimation can be posed as the problem of finding the minimum grey level variance axis within a local neighbourhood. In 2D image signals, this corresponds to the eigensystem analysis of a 2 × 2-tensor, which yields valid results for single orientations. We describe extensions to multiple overlaid orientations, which may be caused...
Conference Paper
Full-text available
Estimation of local orientation in images is often posed as the task of finding the minimum variance axis in a local neighborhood. The solution is given as the eigenvector belonging to the smaller eigenvalue of a 2×2 tensor. Ideally, the tensor is rank-deficient, i.e., the smaller eigenvalue is zero. A large minimal eigenvalue signals the presence...
Article
Full-text available
Local orientation estimation can be posed as the problem of finding the minimum grey level variance axis within a local neighbourhood. In 2D image signals, this corresponds to the eigensystem analysis of a 22-tensor, which yields valid results for single orientations. We describe extensions to multiple overlaid orientations, which may be caused by...
Article
Full-text available
Based on a new framework for the description of N transparent motions we categorize different types of transparent-motion patterns. Confidence measures for the presence of all these classes of patterns are defined in terms of the ranks of the generalized structure tensor. To resolve the correspondence between the ranks of the tensors and the motion...
Article
Full-text available
We first review theoretical results for the problem of estimating single and multiple transparent motions. For N motions we obtain a MM generalized structure tensor JN with M = 3 for one, M = 6 for two, and M = 10 for three motions. The analysis of motion patterns is based on the ranks of JN and is thus not only conceptual but provides computable c...
Article
Full-text available
We extend a novel framework for the estimation of multiple transparent motions to include regularization. We use mixed-motion parameters to obtain linear Euler-Lagrange equations with a regularization term. The equations are solved iteratively for the mixed-motion parameters based on an update rule that is similar to the case of only one motion. Th...
Article
Full-text available
This paper deals with the problem of estimating multiple transparent motions that can occur in computer vision applications, e.g. in the case of semi-transparencies and occlusions, and also in medical imaging when di#erent layers of tissue move independently. Methods based on the known optical-flow equation for two motions are extended in three way...
Article
Full-text available
This paper deals with the problem of estimating multiple motions at points where these motions are overlaid. We present a new approach that is based on block-matching and can deal with both transparent motions and occlusions. We derive a block-matching constraint for an arbitrary number of moving layers. We use this constraint to design a hierarchi...
Conference Paper
Full-text available
Motion estimation is essential in a variety of image process- ing and computer vision tasks, like video coding, tracking, directional ltering and denoising, scene analysis, etc. Transparent motions are ad- ditive or multiplicative superpositions of moving patterns and occur due to reections, semi-transparencies, and partial occlusions. The estima-...
Article
Full-text available
This paper deals with the problem of estimating multiple motions at points where these motions are overlaid. We present a new approach that is based on block-matching and can deal with both transparent motions and occlusions. We derive a block-matching constraint for an arbitrary number of moving layers. We use this constraint to design a hierarchi...
Conference Paper
Full-text available
We present a spatio-temporal analysis of motion at occluding boundaries as an extension of previous results for trans- parent motions. We show how these new results generalize alternative approaches derived in the Fourier domain that are limited by assuming straight occlusion boundaries. Furthermore, we derive a novel hierarchical algorithm that ca...
Conference Paper
Full-text available
We extend a novel framework for the estimation of multiple transparent motions to include regularization. We use mixed-motion parameters to obtain linear Euler-Lagrange equations with a regularization term. The equations are solved iteratively for the mixed-motion parameters based on an update rule that is similar to the case of only one motion. Th...
Conference Paper
Full-text available
This paper deals with the problem of estimating multiple motions at points where these motions are overlaid. We present a new approach that is based on block matching and can deal with both transparent motions and occlusions. We derive a block matching constraint for an arbitrary number of moving layers. Such constraint comes from the theory of mot...
Article
Full-text available
We briefly review a recent development in the area of computer vision and multidimensional signal processing. Image sequences are regarded as hypersurfaces and useful properties are derived from the geometry of that hypersurface. Besides demonstrating the uniqueness of curvature, new methods for the analysis of single and multiple motions are prese...
Conference Paper
Full-text available
A novel framework for single and multiple motion estimation is presented. It is based on a generalized structure tensor that contains blurred products of directional derivatives. The order of differentiation increases with the number of motions but more general linear filters can be used instead of derivatives. From the general framework, a hierarc...
Article
Full-text available
We study the perceptual problem related to image quantization from an optimization point of view, using different metrics on the color space. A consequence of the results presented is that quantization using histogram equalization provides optimal perceptual results. This fact is well known and widely used but, to our knowledge, a proof has never a...
Article
Full-text available
This paper introduces techniques of Riemannian geometry for processing and visualising volumetric graphical objects. A family of non-linear high-pass filters, based on the curvature tensor, is introduced and used to study the local redundancy on objects. It is shown how to reconstruct an object from geometric nonredundant regions and applications a...
Conference Paper
Full-text available
We study the problem of reconstructing an image from a perceptual segmentation based on a geometric classification of its points using non-linear curvature filters. We give a mathematical proof that an image can be reconstructed from the regions of non-zero Gaussian curvatures. This result provides the theoretical background for a new theory of non...
Article
Full-text available
In this paper we exploit the power of contractive mappings to create special image efects. Under this framework, images are represented as the attractor of an Iterated Function System (IFS) and can be reconstructed using Fractal Interpolation. By controlling parameters of the process, we obtain a wide range of image efects. Keywords: Image efects;...

Network

Cited By

Projects

Projects (2)
Archived project
To develop methods for the estimation of two or more orientations in images or two or more motions in image sequences.
Project
End-stopping is a frequent characteristic of cells in mammalian visual system. Such cells can not be modeled by linear functionals and, accordingly, non-linear models have been proposed. A thorough study of such models both in their mathematical and computations aspects has not yet been performed. This project aims to contribute to such study.