Completed Local Structure Patterns on Three Orthogonal Planes for Dynamic Texture Recognition

International audienceDynamic texture (DT) is a challenging problem in computer vision because of the chaotic motion of textures. We address in this paper a new dynamic texture operator by considering local structure patterns (LSP) and completed local binary patterns (CLBP) for static images in three orthogonal planes to capture spatial-temporal texture structures. Since the typical operator of local binary patterns (LBP), which uses center pixel for thresholding, has some limitations such as sensitivity to noise and near uniform regions, the proposed approach can deal with these drawbacks by using global and local texture information for adaptive thresholding and CLBP for exploiting complementary texture information in three orthogonal planes. Evaluations on different datasets of dynamic textures (UCLA, DynTex, DynTex++) show that our proposal significantly outper-forms recent results in the state-of-the-art approaches

Directional Dense-Trajectory-based Patterns for Dynamic Texture Recognition

International audienceRepresentation of dynamic textures (DTs), well-known as a sequence of moving textures, is a challenging problem in video analysis due to disorientation of motion features. Analyzing DTs to make them "under-standable" plays an important role in different applications of computer vision. In this paper, an efficient approach for DT description is proposed by addressing the following novel concepts. First, beneficial properties of dense trajectories are exploited for the first time to efficiently describe DTs instead of the whole video. Second, two substantial extensions of Local Vector Pattern operator are introduced to form a completed model which is based on complemented components to enhance its performance in encoding directional features of motion points in a trajectory. Finally, we present a new framework, called Directional Dense Trajectory Patterns , which takes advantage of directional beams of dense trajectories along with spatio-temporal features of their motion points in order to construct dense-trajectory-based descriptors with more robustness. Evaluations of DT recognition on different benchmark datasets (i.e., UCLA, DynTex, and DynTex++) have verified the interest of our proposal

Numerical analysis of subsoil-reinforced concrete slab interaction

This article presents the numerical modeling of interaction between a reinforced concrete slab and subsoil using ABAQUS. Subsoil was simulated as both homogeneous half-space and inhomogeneous half-space. Reinforcement bars in the concrete slab were accurately modelled allowing capturing a precise deformation profile of the slab in interaction with subsoil. Input data for numerical analysis were adopted from a published work. Results of the study were verified on the basis of comparison with those of the previous study

Towards Design of High Spin Metal-free Materials

In this paper, in order to explore high-spin carbon-based magnetic materials with strong ferromagnetic coupling, geometric structure, electronic structure and magnetic properties of alternating stacks of $\pi$-radical-halogenated-hydrocarbons and diamagnetic molecules have been investigated based on density-functional theory with dispersion correction. These alternating stacks are predicted to avoid the typical antiferromagnetic spin-exchange of indentical face-to-face radicals via spin polarization of a diamagnetic molecule in between. Our results show that $\pi$-radical-halogenated-hydrocarbons like perchlorophenalenyl (C$_{13}$Cl$_{9})$ is strong ferromagnetic coupling if alternatingly stacked with aromatics like fluorinated coronene (C$_{24}$F$_{12})$ or coronene (C$_{24}$H$_{12})$, while fluorinated perinaphthenyl (C$_{13}$F$_{9})$ and perinaphthenyl (C$_{13}$H$_{9})$ are not an equally good choice. The role of ligand configuration in determining exchange coupling in stacks is discussed. These results would give some hints for designing new high-spin carbon-based ferromagnetic materials

Trigonometric weighted generalized convolution operator associated with Fourier cosine-sine and Kontorovich-Lebedev transformations

The main objective of this work is to introduce the generalized convolution with trigonometric weighted $\gamma=\sin y$ involving the Fourier cosine-sine and Kontorovich-Lebedev transforms, and to study its fundamental results. We establish boundedness properties in a two-parametric family of Lebesgue spaces for this convolution operator. Norm estimation in the weighted $L_p$ space is obtained and applications of the corresponding class of convolution integro-differential equations are discussed. The conditions for the solvability of these equations in $L_1$ space are also founded.Comment: 12 page

Vers un modèle de vérification de la couche logique d'entreprise dans une architecture à 3 couches: modèle CPN-ECA

International audienceThis paper proposes a model for building a flexible system, which accepts and verifies the change on business logic, including both business processes and business rules, while the system has to cover the properties as reliability and reuse. In this model, the business process will be designed with Colour Petri Net and translated into a set of Event-Condition-Action rules, this set will be combined with business rules for checking the respect of a business process to the business rules in design and modifying the process. Hierarchical Colour Petri Net is also used to guarantee the reliability and to reuse properties of the system.Ce document propose un modèle pour la création d'un système flexible, qui accepte et vérifie les modifications apportées à la logique métier, y compris les processus et les règles métier, tandis que le système doit couvrir les propriétés en termes de fiabilité et de réutilisation. Dans ce modèle, le processus de gestion sera conçu avec un réseau Pétri coloré et traduit en un ensemble de règles Event-Condition-Action (ECA). Cet ensemble sera combiné à des règles de gestion permettant de vérifier le respect du processus de gestion par modifier le processus. Un réseau Pétri coloré hiérarchisé est également utilisé pour garantir la fiabilité et pour réutiliser les propriétés du systèm

Volumes of Blurred-Invariant Gaussians for Dynamic Texture Classification

International audienceAn effective model, which jointly captures shape and motion cues, for dynamic texture (DT) description is introduced by taking into account advantages of volumes of blurred-invariant features in three main following stages. First, a 3-dimensional Gaussian kernel is used to form smoothed sequences that allow to deal with well-known limitations of local encoding such as near uniform regions and sensitivity to noise. Second , a receptive volume of the Difference of Gaussians (DoG) is figured out to mitigate the negative impacts of environmental and illumination changes which are major challenges in DT understanding. Finally, a local encoding operator is addressed to construct a discriminative descriptor of enhancing patterns extracted from the filtered volumes. Evaluations on benchmark datasets (i.e., UCLA, DynTex, and DynTex++) for issue of DT classification have positively validated our crucial contributions