Designing nanoparticles during the drawing step

International audienceNanoparticles in the core of optical fibres are widely studied due to the opportunity they give to tailor spectroscopic properties. Such fibres are usually obtained by drawing at high temperature a preform containing nanoparticles. This study focuses on the effect of the fibre drawing on nanoparticles. We fabricated an MCVD optical preform by doping the porous layer with nanoparticles. The optical fibre was studied by a FIB/SEM tomography.Figure 1 is the volume reconstruction of the core of the optical fibre. The yellow phase represents nanoparticles inside the core of the optical fibre. This reconstruction shows evidences of break-up, elongation and coalescence of particles. These features will be discussed according to phenomena well known from the rheology of emulsions and polymers. It comes from a competition between viscous stresses of the flow and surface tension.Observation of these size-controlling phenomena occuring during fibre drawing offer new perspectives to tailor the size of nanoparticles and are therefore of great interest for light scattering issues

Traffic extreme situations detection in video sequences based on integral optical flow

Road traffic analysis is an important task in many applications and it can be used in video surveillance systems to prevent many undesirable events. In this paper, we propose a new method based on integral optical flow to analyze cars movement in video and detect flow extreme situations in real-world videos. Firstly, integral optical flow is calculated for video sequences based on optical flow, thus random background motion is eliminated; secondly, pixel-level motion maps which describe cars movement from different perspectives are created based on integral optical flow; thirdly, region-level indicators are defined and calculated; finally, threshold segmentation is used to identify different cars movements. We also define and calculate several parameters of moving car flow including direction, speed, density, and intensity without detecting and counting cars. Experimental results show that our method can identify cars directional movement, cars divergence and cars accumulation effectively.The work was funded by Public Welfare Technology Applied Research Program of Zhejiang Province (LGF19F020016, LGJ18F020001 and LGJ19F020002), Zhejiang Provincial Natural Science Foundation of China (LZ15F020001), and the National High-end Foreign Experts Program (GDW20183300463)

Identifying First-person Camera Wearers in Third-person Videos

We consider scenarios in which we wish to perform joint scene understanding, object tracking, activity recognition, and other tasks in environments in which multiple people are wearing body-worn cameras while a third-person static camera also captures the scene. To do this, we need to establish person-level correspondences across first- and third-person videos, which is challenging because the camera wearer is not visible from his/her own egocentric video, preventing the use of direct feature matching. In this paper, we propose a new semi-Siamese Convolutional Neural Network architecture to address this novel challenge. We formulate the problem as learning a joint embedding space for first- and third-person videos that considers both spatial- and motion-domain cues. A new triplet loss function is designed to minimize the distance between correct first- and third-person matches while maximizing the distance between incorrect ones. This end-to-end approach performs significantly better than several baselines, in part by learning the first- and third-person features optimized for matching jointly with the distance measure itself

Perception of Motion and Architectural Form: Computational Relationships between Optical Flow and Perspective

Perceptual geometry refers to the interdisciplinary research whose objectives focuses on study of geometry from the perspective of visual perception, and in turn, applies such geometric findings to the ecological study of vision. Perceptual geometry attempts to answer fundamental questions in perception of form and representation of space through synthesis of cognitive and biological theories of visual perception with geometric theories of the physical world. Perception of form, space and motion are among fundamental problems in vision science. In cognitive and computational models of human perception, the theories for modeling motion are treated separately from models for perception of form.Comment: 10 pages, 13 figures, submitted and accepted in DoCEIS'2012 Conference: http://www.uninova.pt/doceis/doceis12/home/home.ph

Modeling Quantum Optical Components, Pulses and Fiber Channels Using OMNeT++

Quantum Key Distribution (QKD) is an innovative technology which exploits the laws of quantum mechanics to generate and distribute unconditionally secure cryptographic keys. While QKD offers the promise of unconditionally secure key distribution, real world systems are built from non-ideal components which necessitates the need to model and understand the impact these non-idealities have on system performance and security. OMNeT++ has been used as a basis to develop a simulation framework to support this endeavor. This framework, referred to as "qkdX" extends OMNeT++'s module and message abstractions to efficiently model optical components, optical pulses, operating protocols and processes. This paper presents the design of this framework including how OMNeT++'s abstractions have been utilized to model quantum optical components, optical pulses, fiber and free space channels. Furthermore, from our toolbox of created components, we present various notional and real QKD systems, which have been studied and analyzed.Comment: Published in: A. F\"orster, C. Minkenberg, G. R. Herrera, M. Kirsche (Eds.), Proc. of the 2nd OMNeT++ Community Summit, IBM Research - Zurich, Switzerland, September 3-4, 201

Direct dark mode excitation by symmetry matching of a single-particle based metasurface

This paper makes evidence for direct dark mode excitation mechanism in a metasurface structure. The dark mode excitation mechanism is entirely determined by structures' symmetry and does not depend on near-field coupling between elements. In our examples, we consider single element based metasurface composed of two V antennas connected in an anti-symmetric arrangement. Both experimental and modeling results show an efficient excitation of magnetic dipolar mode in such structures. The direct dark mode excitation mechanism provides a design that is more robust with respect to technology imperfections. The considered approach opens promising perspectives for new type of nanostructure designs and greatly relaxes fabrication constraints for the optical domain.Comment: 21 pages, 5 figure