Deep Learning for Action and Gesture Recognition in Image Sequences: A Survey

Interest in automatic action and gesture recognition has grown considerably in the last few years. This is due in part to the large number of application domains for this type of technology. As in many other computer vision areas, deep learning based methods have quickly become a reference methodology for obtaining state-of-the-art performance in both tasks. This chapter is a survey of current deep learning based methodologies for action and gesture recognition in sequences of images. The survey reviews both fundamental and cutting edge methodologies reported in the last few years. We introduce a taxonomy that summarizes important aspects of deep learning for approaching both tasks. Details of the proposed architectures, fusion strategies, main datasets, and competitions are reviewed. Also, we summarize and discuss the main works proposed so far with particular interest on how they treat the temporal dimension of data, their highlighting features, and opportunities and challenges for future research. To the best of our knowledge this is the first survey in the topic. We foresee this survey will become a reference in this ever dynamic field of research

Influence of Scalar-Relativistic and Spin-Orbit Terms on the Plasmonic Properties of Pure and Silver-Doped Gold Chains

The unique plasmonic character of silver and gold nanoparticles has a wide range of applications, and tailoring this property by changing electronic and geometric structures has received a great deal of attention. Herein, we study the role of the quantum properties in controlling the plasmonic excitations of gold and silver atomic chains and rods. The influence of relativistic effects, scalar as well as spin-orbit, on the intensity and energy of plasmonic excitations is investigated. The intensity quenching and the red shift of energy in the presence of relativistic effects are introduced via the appearance of d orbitals directly in optical excitations in addition to the screening of s-electrons by mixing with the occupied orbitals. For the linear gold system, it will be demonstrated that by increasing the length the relativistic behavior declines and the contribution of d orbitals to the plasmonic excitations evidently decreases. Furthermore, silver atoms are doped in gold chains and rods (with two different arrangements) to realize how gold-silver interactions decrease the relativistic effects and enhance the intensity of collective excitations. Finally, to strengthen the plasmonic behavior of gold, the elongation of chain and doping with suitable atoms such as silver (with the classical plasmonic behavior) can be introduced as the manipulating ways to control the influence of scalar-relativistic and spin-orbit effects and, consequently, reinforce the plasmonic properties

Characterization and modeling of plasma sheath in 2.45 GHz hydrogen ECR ion sources

In this article, we present a multi-fluid numerical model developed for application on electron cyclotron resonance ion sources (ECRIS). The 1D-model is matured to compute the density of the ion species in the plasma sheath in the presence of an inhomogeneous magnetic field of a 2.45 GHz ECRIS. The multi-fluid model in cylindrical coordinates is focused on solving the continuity and momentum equations of hydrogen plasma particles to characterize their sheath properties. In addition, 28 important processes, including volume and surface collisions, have been included in the COMSOL Multiphysics package to simulate the ECR plasma. We study the elementary processes containing electron–atom, electron–molecule, atom–molecule, molecule–molecule, and particle–wall interactions. Then, the results of the model and the simulation of a 2D-hydrogen plasma are reported, and future perspectives are discussed throughout the paper