Electric field enhancement with plasmonic colloidal nanoantennas excited by a silicon nitride waveguide

We investigate the feasibility of CMOS-compatible optical structures to develop novel integrated spectroscopy systems. We show that local field enhancement is achievable utilizing dimers of plasmonic nanospheres that can be assembled from colloidal solutions on top of a CMOS-compatible optical waveguide. The resonant dimer nanoantennas are excited by modes guided in the integrated silicon nitride waveguide. Simulations show that 100 fold electric field enhancement builds up in the dimer gap as compared to the waveguide evanescent field amplitude at the same location. We investigate how the field enhancement depends on dimer location, orientation, distance and excited waveguide modes

Low and Variable Frame Rate Face Tracking Using an IP PTZ Camera

RÉSUMÉ En vision par ordinateur, le suivi d'objets avec des caméras PTZ a des applications dans divers domaines, tels que la surveillance vidéo, la surveillance du trafic, la surveillance de personnes et la reconnaissance de visage. Toutefois, un suivi plus précis, efficace, et fiable est requis pour une utilisation courante dans ces domaines. Dans cette thèse, le suivi est appliqué au haut du corps d'un humain, en incluant son visage. Le suivi du visage permet de déterminer son emplacement pour chaque trame d'une vidéo. Il peut être utilisé pour obtenir des images du visage d'un humain dans des poses différentes. Dans ce travail, nous proposons de suivre le visage d'un humain à l’aide d'une caméra IP PTZ (caméra réseau orientable). Une caméra IP PTZ répond à une commande via son serveur Web intégré et permet un accès distribué à partir d'Internet. Le suivi avec ce type de caméra inclut un bon nombre de défis, tels que des temps de réponse irrégulier aux commandes de contrôle, des taux de trame faibles et irréguliers, de grand mouvements de la cible entre deux trames, des occlusions, des modifications au champ de vue, des changements d'échelle, etc. Dans notre travail, nous souhaitons solutionner les problèmes des grands mouvements de la cible entre deux trames consécutives, du faible taux de trame, des modifications de l'arrière-plan, et du suivi avec divers changements d'échelle. En outre, l'algorithme de suivi doit prévoir les temps de réponse irréguliers de la caméra. Notre solution se compose d’une phase d’initialisation pour modéliser la cible (haut du corps), d’une adaptation du filtre de particules qui utilise le flux optique pour générer des échantillons à chaque trame (APF-OFS), et du contrôle de la caméra. Chaque composante exige des stratégies différentes. Lors de l'initialisation, on suppose que la caméra est statique. Ainsi, la détection du mouvement par soustraction d’arrière-plan est utilisée pour détecter l'emplacement initial de la personne. Ensuite, pour supprimer les faux positifs, un classificateur Bayesien est appliqué sur la région détectée afin de localiser les régions avec de la peau. Ensuite, une détection du visage basée sur la méthode de Viola et Jones est effectuée sur les régions de la peau. Si un visage est détecté, le suivi est lancé sur le haut du corps de la personne.----------ABSTRACT Object tracking with PTZ cameras has various applications in different computer vision topics such as video surveillance, traffic monitoring, people monitoring and face recognition. Accurate, efficient, and reliable tracking is required for this task. Here, object tracking is applied to human upper body tracking and face tracking. Face tracking determines the location of the human face for each input image of a video. It can be used to get images of the face of a human target under different poses. We propose to track the human face by means of an Internet Protocol (IP) Pan-Tilt-Zoom (PTZ) camera (i.e. a network-based camera that pans, tilts and zooms). An IP PTZ camera responds to command via its integrated web server. It allows a distributed access from Internet (access from everywhere, but with non-defined delay). Tracking with such camera includes many challenges such as irregular response times to camera control commands, low and irregular frame rate, large motions of the target between two frames, target occlusion, changing field of view (FOV), various scale changes, etc. In our work, we want to cope with the problem of large inter-frame motion of targets, low usable frame rate, background changes, and tracking with various scale changes. In addition, the tracking algorithm should handle the camera response time and zooming. Our solution consists of a system initialization phase which is the processing before camera motion and a tracker based on an Adaptive Particle Filter using Optical Flow based Sampling (APF-OFS) tracker, and camera control that are the processing after the motion of the camera. Each part requires different strategies. For initialization, when the camera is stationary, motion detection for a static camera is used to detect the initial location of the person face entering an area. For motion detection in the FOV of the camera, a background subtraction method is applied. Then to remove false positives, Bayesian skin classifier is applied on the detected motion region to discriminate skin regions from non skin regions. Face detection based on Viola and Jones face detector can be performed on the detected skin regions independently of their face size and position within the image

Two-scale structure for giant field enhancement: combination of Rayleigh anomaly and colloidal plasmonic resonance

We demonstrate theoretically and experimentally a two-scale architecture able to achieve giant field enhancement by simultaneously exploiting both the Rayleigh anomaly and localized surface plasmon resonance. Metallic oligomers composed of colloidal nanospheres are well-known for the ability to strongly enhance the near-field at their plasmonic resonance. However, due to intrinsic nonlocality of the dielectric response of the metals along with their inherent loss, the achievable field enhancement has an ultimate constraint. In this paper we demonstrate that combining plasmonic resonance enhancements from oligomers, with feature size of tens of nanometers, with a Rayleigh anomaly caused by a 1-D set of periodic nanorods, having a period on the order of the excitation wavelength, provides a mean to produce enhancement beyond that constrained by losses in near field resonances. Metallic oligomers are chemically assembled in between the periodic set of nanorods that are fabricated using lithographic methods. The nanorod periodicity is investigated to induce the Rayleigh anomaly at the oligomers plasmonic resonance wavelength to further enhance the field in the oligomers hot spots. A thorough study of this structure is carried out by using an effective analytical-numerical model which is also compared to full-wave simulation results. Experimental results comparing enhancements in surface enhanced Raman scattering measurements with and without nanorods demonstrate the effectiveness of a Rayleigh anomaly in boosting the field enhancement. The proposed structure is expected to be beneficial for many applications ranging from medical diagnostics to sensors and solar cells

A Multiscale Region-Based Motion Detection and Background Subtraction Algorithm

This paper presents a region-based method for background subtraction. It relies on color histograms, texture information, and successive division of candidate rectangular image regions to model the background and detect motion. Our proposed algorithm uses this principle and combines it with Gaussian Mixture background modeling to produce a new method which outperforms the classic Gaussian Mixture background subtraction method. Our method has the advantages of filtering noise during image differentiation and providing a selectable level of detail for the contour of the moving shapes. The algorithm is tested on various video sequences and is shown to outperform state-of-the-art background subtraction methods

FPGA Implementation for Real-Time Background Subtraction Based on Horprasert Model

Background subtraction is considered the first processing stage in video surveillance systems, and consists of determining objects in movement in a scene captured by a static camera. It is an intensive task with a high computational cost. This work proposes an embedded novel architecture on FPGA which is able to extract the background on resource-limited environments and offers low degradation (produced because of the hardware-friendly model modification). In addition, the original model is extended in order to detect shadows and improve the quality of the segmentation of the moving objects. We have analyzed the resource consumption and performance in Spartan3 Xilinx FPGAs and compared to others works available on the literature, showing that the current architecture is a good trade-off in terms of accuracy, performance and resources utilization. With less than a 65% of the resources utilization of a XC3SD3400 Spartan-3A low-cost family FPGA, the system achieves a frequency of 66.5 MHz reaching 32.8 fps with resolution 1,024 × 1,024 pixels, and an estimated power consumption of 5.76 W

An Efficient Direction Field-Based Method for the Detection of Fasteners on High-Speed Railways

Railway inspection is an important task in railway maintenance to ensure safety. The fastener is a major part of the railway which fastens the tracks to the ground. The current article presents an efficient method to detect fasteners on the basis of image processing and pattern recognition techniques, which can be used to detect the absence of fasteners on the corresponding track in high-speed(up to 400 km/h). The Direction Field is extracted as the feature descriptor for recognition. In addition, the appropriate weight coefficient matrix is presented for robust and rapid matching in a complex environment. Experimental results are presented to show that the proposed method is computation efficient and robust for the detection of fasteners in a complex environment. Through the practical device fixed on the track inspection train, enough fastener samples are obtained, and the feasibility of the method is verified at 400 km/h

Background Subtraction Based on Color and Depth Using Active Sensors

Depth information has been used in computer vision for a wide variety of tasks. Since active range sensors are currently available at low cost, high-quality depth maps can be used as relevant input for many applications. Background subtraction and video segmentation algorithms can be improved by fusing depth and color inputs, which are complementary and allow one to solve many classic color segmentation issues. In this paper, we describe one fusion method to combine color and depth based on an advanced color-based algorithm. This technique has been evaluated by means of a complete dataset recorded with Microsoft Kinect, which enables comparison with the original method. The proposed method outperforms the others in almost every test, showing more robustness to illumination changes, shadows, reflections and camouflage.This work was supported by the projects of excellence from Junta de Andalucia MULTIVISION (TIC-3873), ITREBA (TIC-5060) and VITVIR (P11-TIC-8120), the national project, ARC-VISION (TEC2010-15396), and the EU Project, TOMSY (FP7-270436)

Characterization of Buoyant Fluorescent Particles for Field Observations of Water Flows

In this paper, the feasibility of off-the-shelf buoyant fluorescent microspheres as particle tracers in turbid water flows is investigated. Microspheres’ fluorescence intensity is experimentally measured and detected in placid aqueous suspensions of increasing concentrations of clay to simulate typical conditions occurring in natural drainage networks. Experiments are conducted in a broad range of clay concentrations and particle immersion depths by using photoconductive cells and image-based sensing technologies. Results obtained with both methodologies exhibit comparable trends and show that the considered particles are fairly detectable in critically turbid water flows. Further information on performance and integration of the studied microspheres in low-cost measurement instrumentation for field observations is obtained through experiments conducted in a custom built miniature water channel. This experimental characterization provides a first assessment of the feasibility of commercially available buoyant fluorescent beads in the analysis of high turbidity surface water flows. The proposed technology may serve as a minimally invasive sensing system for hazardous events, such as pollutant diffusion in natural streams and flash flooding due to extreme rainfall

Optical Nanoantennas for Sensors, Microscopy and Spectroscopy

Metallic nanosctructures possess electromagnetic properties useful for various applications, such as surface enhanced Raman spectroscopy (SERS), harmonic generation and solar cells. Specifically, because of their ability in confining electromagnetic fields to nanoscopic dimensions, they provide an exquisite platform for conducting studies on molecules placed in their vicinity. In this dissertation, I introduce and study various plasmonic nanostructures to achieve electric and magnetic field enhancement for spectroscopy and microscopy applications. First, I investigate feasibility of CMOS-compatible optical structures to develop novel integrated spectroscopy systems. I show that local field enhancement is achievable utilizing dimers of plasmonic nanospheres that can be assembled from colloidal solutions on top of a CMOS-compatible optical waveguide. The resonant dimer nanoantennas are excited by modes guided in the integrated silicon nitride waveguide. Specifically, I investigate how the field enhancement depends on dimer location, orientation, distance and excited waveguide mode. However, the field enhancement achievable with using oligomers is limited due to inherent losses of plasmonic particles. Thus, I study a novel structure called two-scale, in which Rayleigh anomaly caused by a 1D set of periodic nanorods is utilized. A thorough study of this structure is carried out by using an effective analytical-numerical model which is also compared to full-wave simulation results. Experimental results comparing enhancements in surface enhanced Raman scattering measurements with and without nanorods demonstrate the effectiveness of a Rayleigh anomaly in boosting the field enhancement.The other side of the dissertation is dedicated to magnetic field enhancement. I propose various metallic and dielectric nanostructures for local magnetic field enhancement at optical frequencies. I show that dielectric structures can be a good alternative for their plasmonic counterpart due to their low loss. The idea behind each structure is supported by results from full-wave simulations. More importantly, I utilize azimuthally polarized beam as a way of boosting local magnetic field and isolating it from electric field. The magnetic field enhancement of these structures can be utilized in studying magnetic dipole transitions, magnetic imaging and enhanced spectroscopy applications