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Author Angel D. Sappa; Juan A. Carvajal; Cristhian A. Aguilera; Miguel Oliveira; Dennis G. Romero; Boris X. Vintimilla
Title Wavelet-Based Visible and Infrared Image Fusion: A Comparative Study Type Journal Article
Year (down) 2016 Publication Sensors Journal Abbreviated Journal
Volume Vol. 16 Issue Pages pp. 1-15
Keywords image fusion; fusion evaluation metrics; visible and infrared imaging; discrete wavelet transform
Abstract This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and LongWave InfraRed (LWIR).
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Call Number cidis @ cidis @ Serial 47
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Author Cristhian A. Aguilera; Francisco J. Aguilera; Angel D. Sappa; Ricardo Toledo
Title Learning crossspectral similarity measures with deep convolutional neural networks Type Conference Article
Year (down) 2016 Publication IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) Workshops Abbreviated Journal
Volume Issue Pages 267-275
Keywords
Abstract The simultaneous use of images from different spectra can be helpful to improve the performance of many com- puter vision tasks. The core idea behind the usage of cross- spectral approaches is to take advantage of the strengths of each spectral band providing a richer representation of a scene, which cannot be obtained with just images from one spectral band. In this work we tackle the cross-spectral image similarity problem by using Convolutional Neural Networks (CNNs). We explore three different CNN archi- tectures to compare the similarity of cross-spectral image patches. Specifically, we train each network with images from the visible and the near-infrared spectrum, and then test the result with two public cross-spectral datasets. Ex- perimental results show that CNN approaches outperform the current state-of-art on both cross-spectral datasets. Ad- ditionally, our experiments show that some CNN architec- tures are capable of generalizing between different cross- spectral domains.
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Call Number cidis @ cidis @ Serial 48
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Author Miguel Oliveira; Vítor Santos; Angel D. Sappa; Paulo Dias; A. Paulo Moreira
Title Incremental Scenario Representations for Autonomous Driving using Geometric Polygonal Primitives Type Journal Article
Year (down) 2016 Publication Robotics and Autonomous Systems Journal Abbreviated Journal
Volume Vol. 83 Issue Pages pp. 312-325
Keywords Incremental scene reconstructionPoint cloudsAutonomous vehiclesPolygonal primitives
Abstract When an autonomous vehicle is traveling through some scenario it receives a continuous stream of sensor data. This sensor data arrives in an asynchronous fashion and often contains overlapping or redundant information. Thus, it is not trivial how a representation of the environment observed by the vehicle can be created and updated over time. This paper presents a novel methodology to compute an incremental 3D representation of a scenario from 3D range measurements. We propose to use macro scale polygonal primitives to model the scenario. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Furthermore, we propose mechanisms designed to update the geometric polygonal primitives over time whenever fresh sensor data is collected. Results show that the approach is capable of producing accurate descriptions of the scene, and that it is computationally very efficient when compared to other reconstruction techniques.
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Call Number cidis @ cidis @ Serial 49
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Author Miguel Oliveira; Vítor Santos; Angel D. Sappa; Paulo Dias; A. Paulo Moreira
Title Incremental Texture Mapping for Autonomous Driving Type Journal Article
Year (down) 2016 Publication Robotics and Autonomous Systems Journal Abbreviated Journal
Volume Vol. 84 Issue Pages pp. 113-128
Keywords Scene reconstruction, Autonomous driving, Texture mapping
Abstract Autonomous vehicles have a large number of on-board sensors, not only for providing coverage all around the vehicle, but also to ensure multi-modality in the observation of the scene. Because of this, it is not trivial to come up with a single, unique representation that feeds from the data given by all these sensors. We propose an algorithm which is capable of mapping texture collected from vision based sensors onto a geometric description of the scenario constructed from data provided by 3D sensors. The algorithm uses a constrained Delaunay triangulation to produce a mesh which is updated using a specially devised sequence of operations. These enforce a partial configuration of the mesh that avoids bad quality textures and ensures that there are no gaps in the texture. Results show that this algorithm is capable of producing fine quality textures.
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Notes Approved no
Call Number cidis @ cidis @ Serial 50
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Author Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic
Title Multi-sensor Fusion Module in a Fault Tolerant Perception System for Autonomous Vehicles Type Journal Article
Year (down) 2016 Publication Journal of Automation and Control Engineering (JOACE) Abbreviated Journal
Volume Vol. 4 Issue Pages pp. 430-436
Keywords Fault Tolerance, Data Fusion, Multi-sensor Fusion, Autonomous Vehicles, Perception System
Abstract Driverless vehicles are currently being tested on public roads in order to examine their ability to perform in a safe and reliable way in real world situations. However, the long-term reliable operation of a vehicle’s diverse sensors and the effects of potential sensor faults in the vehicle system have not been tested yet. This paper is proposing a sensor fusion architecture that minimizes the influence of a sensor fault. Experimental results are presented simulating faults by introducing displacements in the sensor information from the KITTI dataset.
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Call Number cidis @ cidis @ Serial 51
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Author Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic
Title A Fault Tolerant Perception system for autonomous vehicles Type Conference Article
Year (down) 2016 Publication 35th Chinese Control Conference (CCC2016), International Conference on, Chengdu Abbreviated Journal
Volume Issue Pages 1-6
Keywords Fault Tolerant Perception, Sensor Data Fusion, Fault Tolerance, Autonomous Vehicles, Federated Architecture
Abstract Driverless vehicles are currently being tested on public roads in order to examine their ability to perform in a safe and reliable way in real world situations. However, the long-term reliable operation of a vehicle’s diverse sensors and the effects of potential sensor faults in the vehicle system have not been tested yet. This paper is proposing a sensor fusion architecture that minimizes the influence of a sensor fault. Experimental results are presented simulating faults by introducing displacements in the sensor information from the KITTI dataset.
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Language English Summary Language English Original Title
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Notes Approved no
Call Number cidis @ cidis @ Serial 52
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Author Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa
Title Fine-tuning based deep covolutional networks for lepidopterous genus recognition Type Conference Article
Year (down) 2016 Publication XXI IberoAmerican Congress on Pattern Recognition Abbreviated Journal
Volume Issue Pages 1-9
Keywords
Abstract This paper describes an image classi cation approach ori- ented to identify specimens of lepidopterous insects recognized at Ecuado- rian ecological reserves. This work seeks to contribute to studies in the area of biology about genus of butter ies and also to facilitate the reg- istration of unrecognized specimens. The proposed approach is based on the ne-tuning of three widely used pre-trained Convolutional Neural Networks (CNNs). This strategy is intended to overcome the reduced number of labeled images. Experimental results with a dataset labeled by expert biologists, is presented|a recognition accuracy above 92% is reached. 1 Introductio
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Call Number cidis @ cidis @ Serial 53
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Author Angel D. Sappa; Cristhian A. Aguilera; Juan A. Carvajal Ayala; Miguel Oliveira; Dennis Romero; Boris X. Vintimilla; Ricardo Toledo
Title Monocular visual odometry: a cross-spectral image fusion based approach Type Journal Article
Year (down) 2016 Publication Robotics and Autonomous Systems Journal Abbreviated Journal
Volume Vol. 86 Issue Pages pp. 26-36
Keywords Monocular visual odometry LWIR-RGB cross-spectral imaging Image fusion
Abstract This manuscript evaluates the usage of fused cross-spectral images in a monocular visual odometry approach. Fused images are obtained through a Discrete Wavelet Transform (DWT) scheme, where the best setup is em- pirically obtained by means of a mutual information based evaluation met- ric. The objective is to have a exible scheme where fusion parameters are adapted according to the characteristics of the given images. Visual odom- etry is computed from the fused monocular images using an off the shelf approach. Experimental results using data sets obtained with two different platforms are presented. Additionally, comparison with a previous approach as well as with monocular-visible/infrared spectra are also provided showing the advantages of the proposed scheme.
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Language Enlgish Summary Language English Original Title
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Notes Approved no
Call Number cidis @ cidis @ Serial 54
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Author Ortiz J.; Londono J.; Novillo F.; Ampuno A.; Chávez M.
Title Determinación de Invariantes en Grandes Centros de Datos basados en Topología Fat-Tree Type Journal Article
Year (down) 2015 Publication Revista Politécnica Abbreviated Journal
Volume Vol. 35 Issue Pages pp. 91-96
Keywords Invariantes de red, topologías, Fat-tree, simulación, emulación
Abstract Durante los últimos años ha existido un fuerte incremento en el acceso a internet, causando que los centros de datos ( DC) deban adaptar dinámicamente su infraestructura de red de cara a enfrentar posibles problemas de congestión, la cual no siempre se da de forma oportuna. Ante esto, nuevas topologías de red se han propuesto en los últimos años, como una forma de brindar mejores condiciones para el manejo de tráfico interno, sin embargo es común que para el estudio de estas mejoras, se necesite recrear el comportamiento de un verdadero DC en modelos de simulación/emulación. Por lo tanto se vuelve esencial validar dichos modelos, de cara a obtener resultados coherentes con la realidad. Esta validación es posible por medio de la identificación de ciertas propiedades que se deducen a partir de las variables y los parámetros que describen la red, y que se mantienen en las topologías de los DC para diversos escenarios y/o configuraciones. Estas propiedades, conocidas como invariantes, son una expresión del funcionamiento de la red en ambientes reales, como por ejemplo la ruta más larga entre dos nodos o el número de enlaces mínimo que deben fallar antes de una pérdida de conectividad en alguno de los nodos de la red. En el presente trabajo se realiza la identificación, formulación y comprobación de dos invariantes para la topología Fat-Tree, utilizando como software emulador a mininet. Las conclusiones muestran resultados concordantes entre lo analítico y lo práctico.
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Publisher Escuela Politécnica Nacional Place of Publication Editor
Language Español Summary Language Español Original Title
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Call Number cidis @ cidis @ Serial 32
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Author Dennys Paillacho; F. Novillo; W. Agila.; V. Huilcapi
Title Impacto de las redes de comunicaciones en los Sistemas Robóticos de Control Type Journal Article
Year (down) 2015 Publication Revista Politécnica Abbreviated Journal
Volume Vol. 35 Issue Pages pp. 97-102
Keywords Ethernet, CAN, Swichted Ethernet, Sistemas de control en red, Ciclo de comunicación, Control de ajuste de trayectoria
Abstract El análisis de incidencia que tienen las redes de comunicaciones sobre el comportamiento de los sistemas robóticos de control en red muestra grandes dificultades cuando se quieren hacer evaluaciones de tipo analítico. Por tal razón, en este trabajo un análisis que utiliza una aproximación basada en simulación es propuesto, de manera que el comportamiento temporal y espacial de un sistema robótico de control en red pueda ser evaluado. Para tal efecto, se propone un entorno de validación mediante el cual una red de comunicaciones permita distribuir mensajes de control entre el controlador principal y los controladores remotos ubicados en cada articulación angular del robot manipulador planar. Las interacciones entre los componentes del sistema han sido modeladas mediante un sistema de capas. Dicho modelo es llevado a un entorno de simulación con la finalidad de analizar el impacto de distintos parámetros de comunicaciones (i.e. tipo de red, tasa de datos y tamaño de datos) sobre el ciclo de comunicación y el error de seguimiento de trayectoria en un sistema robótico.
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Corporate Author Thesis
Publisher Escuela Politécnica Nacional Place of Publication Editor
Language Español Summary Language Español Original Title
Series Editor Series Title Abbreviated Series Title
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Notes Approved no
Call Number cidis @ cidis @ Serial 33
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