A computational model of texture segmentation

An algorithm for finding texture boundaries in images is developed on the basis of a computational model of human texture perception. The model consists of three stages: (1) the image is convolved with a bank of even-symmetric linear filters followed by half-wave rectification to give a set of responses; (2) inhibition, localized in space, within and among the neural response profiles results in the suppression of weak responses when there are strong responses at the same or nearby locations; and (3) texture boundaries are detected using peaks in the gradients of the inhibited response profiles. The model is precisely specified, equally applicable to grey-scale and binary textures, and is motivated by detailed comparison with psychophysics and physiology. It makes predictions about the degree of discriminability of different texture pairs which match very well with experimental measurements of discriminability in human observers. From a machine-vision point of view, the scheme is a high-quality texture-edge detector which works equally on images of artificial and natural scenes. The algorithm makes the use of simple local and parallel operations, which makes it potentially real-time

Preattentive texture discrimination with early vision mechanisms

We present a model of human preattentive texture perception. This model consists of three stages: (1) convolution of the image with a bank of even-symmetric linear filters followed by half-wave rectification to give a set of responses modeling outputs of V1 simple cells, (2) inhibition, localized in space, within and among the neural-response profiles that results in the suppression of weak responses when there are strong responses at the same or nearby locations, and (3) texture-boundary detection by using wide odd-symmetric mechanisms. Our model can predict the salience of texture boundaries in any arbitrary gray-scale image. A computer implementation of this model has been tested on many of the classic stimuli from psychophysical literature. Quantitative predictions of the degree of discriminability of different texture pairs match well with experimental measurements of discriminability in human observers

Non Uniform Multiresolution Method for Optical Flow and Phase Portrait Models: Environmental Applications

Projet AIRIn this paper we define a complete framework for processing large image sequences for a global monitoring of short range oceanographic and atmospheric processes. This framework is based on the use of a non quadratic regularization technique in optical flow computation that preserves flow discontinuities. We also show that using an appropriate tessellation of the image according to an estimate of the motion field can improve optical flow accuracy and yields more reliable flows. This method defines a non uniform multiresolution approach for coarse to fine grid generation. It allows to locally increase the resolution of the grid according to the studied problem. Each added node refines the grid in a region of interest and increases the numerical accuracy of the solution in this region. We make use of such a method for solving the optical flow equation with a non quadratic regularization scheme allowing the computation of optical flow field while preserving its discontinuities. The second part of the paper deals with the interpretation of the obtained displacement field. We make use of a phase portrait model with a new formulation of the approximation of an oriented flow field allowing to consider arbitrary polynomial phase portrait models for characterizing salient flow features. This new framework is used for processing oceanographic and atmospheric image sequences and presents an alternative to complex physical modeling techniques

Magnetic structures and reorientation transitions in noncentrosymmetric uniaxial antiferromagnets

A phenomenological theory of magnetic states in noncentrosymmetric tetragonal antiferromagnets is developed, which has to include homogeneous and inhomogeneous terms (Lifshitz-invariants) derived from Dzyaloshinskii-Moriya couplings. Magnetic properties of this class of antiferromagnets with low crystal symmetry are discussed in relation to its first known members, the recently detected compounds Ba2CuGe2O7 and K2V3O8. Crystallographic symmetry and magnetic ordering in these systems allow the simultaneous occurrence of chiral inhomogeneous magnetic structures and weak ferromagnetism. New types of incommensurate magnetic structures are possible, namely, chiral helices with rotation of staggered magnetization and oscillations of the total magnetization. Field-induced reorientation transitions into modulated states have been studied and corresponding phase diagrams are constructed. Structures of magnetic defects (domain-walls and vortices) are discussed. In particular, vortices, i.e. localized non-singular line defects, are stabilized by the inhomogeneous Dzyaloshinskii-Moriya interactions in uniaxial noncentrosymmetric antiferromagnets.Comment: 18 pages RevTeX4, 13 figure

ReliTalk: Relightable Talking Portrait Generation from a Single Video

Recent years have witnessed great progress in creating vivid audio-driven portraits from monocular videos. However, how to seamlessly adapt the created video avatars to other scenarios with different backgrounds and lighting conditions remains unsolved. On the other hand, existing relighting studies mostly rely on dynamically lighted or multi-view data, which are too expensive for creating video portraits. To bridge this gap, we propose ReliTalk, a novel framework for relightable audio-driven talking portrait generation from monocular videos. Our key insight is to decompose the portrait's reflectance from implicitly learned audio-driven facial normals and images. Specifically, we involve 3D facial priors derived from audio features to predict delicate normal maps through implicit functions. These initially predicted normals then take a crucial part in reflectance decomposition by dynamically estimating the lighting condition of the given video. Moreover, the stereoscopic face representation is refined using the identity-consistent loss under simulated multiple lighting conditions, addressing the ill-posed problem caused by limited views available from a single monocular video. Extensive experiments validate the superiority of our proposed framework on both real and synthetic datasets. Our code is released in https://github.com/arthur-qiu/ReliTalk

Face Liveness Detection for Biometric Antispoofing Applications using Color Texture and Distortion Analysis Features

Face recognition is a widely used biometric approach. Face recognition technology has developed rapidly in recent years and it is more direct, user friendly and convenient compared to other methods. But face recognition systems are vulnerable to spoof attacks made by non-real faces. It is an easy way to spoof face recognition systems by facial pictures such as portrait photographs. A secure system needs Liveness detection in order to guard against such spoofing. In this work, face liveness detection approaches are categorized based on the various types techniques used for liveness detection. This categorization helps understanding different spoof attacks scenarios and their relation to the developed solutions. A review of the latest works regarding face liveness detection works is presented. The main aim is to provide a simple path for the future development of novel and more secured face liveness detection approach

Aspects of Complex Magnetism: Vortex Phases, Skyrmion Dynamics, and Chaotic Nano-Oscillators

Project I Vortex Phase in Spiral Antiferromagnets Spiral antiferromagnets are characterized by a Dzyaloshinskii-Moriya interaction that stabilizes spatially modulated phases of the staggered order parameter. In the framework of a Ginzburg-Landau theory, it is shown that a magnetic field leads to the formation of a topological phase constituting a square lattice of vortices and antivortices. An orthogonal alignment of the antiferromagnetic staggered order parameter with an external magnetic field is energetically favorable since both sublattices of a spiral antiferromagnet cannot minimize their Zeeman energy simultaneously, and energy can be gained from spin canting. This spin-flop mechanism has the same effect as easy-plane anisotropy, which leads the vortices to form topological defects with vanishing core. Thus, the vortex phase is only stable close to the Néel temperature. At lower temperatures, the square-lattice vortex phase undergoes spontaneous symme- try breaking into a rectangular phase. We investigate the stability of this rectangular phase with respect to mixed DMI and in-plane magnetic fields. Since any modulated magnetic texture induces a ferroelectric polarization, the vortices of both the vortex and the rectangular phase carry an electrical charge which makes them amenable to the ma- nipulation with in-plane electric fields. Finally, the relevance of these results for the chiral antiferromagnet Ba2CuGe2O7 is discussed. Project II High-Energy Magnons of a Skyrmion Lattice The energy bands of magnons in the skyrmion lattice phase of a chiral magnet, which were recently measured experimentally, show a peculiar, parabola-shaped superstructure when plotted in an extended zone scheme. They are described theoretically in the con- tinuum approximation by a bosonic Bogoliubov-de Gennes equation. In this project, a high-energy approximation is developed, which takes the form of a Schrödinger equa- tion, describing these magnons as charged particles in the emergent magnetic field of the skyrmion lattice. It is known that charged particles in a periodically modulated magnetic field can form runaway orbits, skipping between regions of positive and regions of negative magnetic field values and effectively behaving as free particles. A semiclassical analysis shows the magnon eigenfunctions corresponding to the parabola-shaped superstructures focus on the runaway orbits in the periodically modulated emergent magnetic field experienced by the magnons in this high-energy description. Hence, they can be explained by classical runaway orbits, skipping along the high-symmetry directions of the skyrmion lattice phase, which may be used as magnon waveguides. Project III Chaotic Spin-Torque Nano-Oscillator A spin current transversing a magnetic material exerts a spin-transfer torque onto the magnetic textures, which may lead to oscillations of the magnetization, which constitutes a so-called spin-torque nano-oscillator. Understanding the dynamics of spin-torque nano- oscillators is a prerequisite for applications in reservoir and stochastic computing and designing hardware that emulates artificial neural networks with low power consumption. This project analyses a specific setup for an antiferromagnetic spin-torque nano-oscillator, where a spin current drives a collinear easy-axis antiferromagnet, including damping, and with an external magnetic field applied perpendicular to it. First, it characterizes the static, uniform states and their excitations, yielding the eigenfrequencies of the nano- oscillator. Next, it analyzes the regular dynamics, investigating the stability of a limit cycle at the spin-flop field. Finally, it is shown by calculating the Lyapunov spectrum that this model features chaotic dynamics intrinsically. The transition to chaos is analyzed us- ing bifurcation diagrams, and it is shown that for large damping, chaos is controlled by period-halving bifurcations