Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

A Visual Programming Framework for Wireless Sensor Networks in Smart Home Applications

International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2015). 7 to 9, Apr, 2015. Singapure, Singapore.

Autonomous Surface Vehicle Docking Manoeuvre with Visual Information

This work presents a hybrid coordinated manoeuvre for docking an autonomous surface vehicle with an autonomous underwater vehicle. The control manoeuvre uses visual information to estimate the AUV relative position and attitude in relation to the ASV and steers the ASV in order to dock with the AUV. The AUV is assumed to be at surface with only a small fraction of its volume visible. The system implemented in the autonomous surface vehicle ROAZ, developed by LSA-ISEP to perform missions in river environment, test autonomous AUV docking capabilities and multiple AUV/ASV coordinated missions is presented. Information from a low cost embedded robotics vision system (LSAVision), along with inertial navigation sensors is fused in an extended Kalman filter and used to determine AUV relative position and orientation to the surface vehicle The real time vision processing system is described and results are presented in operational scenario.

O treino da perceção visual e da consciência fonológica como promotor da fluência da leitura num aluno do 2º ciclo do ensino básico

Aprender a ler é um dos maiores desafios que as crianças enfrentam quando entram para a escola. A dificuldade no domínio do código alfabético, nos níveis da consciência fonológica e a falta de fluência na leitura são fatores que interferem em larga escala na aprendizagem global dos alunos. Habilitar um aluno para a prática da leitura é um estímulo que tem vindo a dar origem a várias investigações e intervenções no campo da educação. Este projeto descreve dois programas de treino: “Programa de treino da percepção Visual” e “Programa de promoção do desenvolvimento da consciência fonológica”, num aluno do 2º ciclo do ensino básico com dificuldade de fluência na leitura, ao longo de quinze aulas de 90 minutos. No que respeita aos resultados do primeiro estudo, que teve por base o “Programa de treino da percepção visual”, não foram encontradas diferenças relevantes quanto ao seu efeito na fluência da leitura do aluno. No entanto, no segundo estudo, que se centrou na aplicação do “Programa de promoção do desenvolvimento da consciência fonológica” em complemento com o “Programa de treino da percepção visual”, mostrou que o aluno ficou mais fluente na leitura diminuindo o número de erros de precisão (substituições, omissões, inversões, adições e erros complexos). Assim, sugere-se uma monotorização sistemática das aprendizagens dos alunos para que as intervenções possam ser cada vez mais precoces e direcionadas para as suas necessidades.

Células Endoteliais e Recuperação Visual

Na revisão bibliográfica encontramos perdas de céluas endoteliais que vão dos 4 aos 25%. Os vários estudos comparam EEC com e sem OVD, EEC e facoemulsificação, cataratas de diferente "dureza", entre outras variáveis. Também a idade, a ruptura do saco ou a perda de vítreo influenciavam estes resultados. As novas tecnologias para facoemulsificação como a peça de mão Ozil torsional que como o nome indica tem a capacidade de movimento torsional lateral (que desbasta a catarata além do movimento longitudinal da peça de mão convencional que emulsifica) torna os gestos cirúrgicos mais eficazes e seguros, reduzindo o traumatismo endotelial. Os AA fizeram um estudo prospectivo em que distribuíram 40 olhos de forma aleatória em dois grupos: 20 olhos foram operados por faco torsional e as restantes 20 cataratas foram operadas por faco convencional. Neste estudo comparativo entre faco torsional e convencional, o primeiro necessitou de menos ultrasons (0,048 versus 0,083), obteve uma acuidade visual média ligeiramente melhor (0,63 versus 0,54) e menor perda celular endotelial (3% versus 6,9%), no 1º dia de pós-operatório. Como se sabe, são múltiplos os factores que influenciam o resultado cirúrgico: o local e tamanho da incisão, a composição das soluções salinas, os dispositivos visco-elásticos, os produtos potencialmente tóxicos aplicados intra-operatoriamente, o tempo de cirurgia, a dureza da catarata, além das técnicas cirúrgicas e dos aparelhos utilizados.

Avaliação da Estereopsia em Crianças sob Terapêutica Oclusiva por Ambliopia e Relação desta com a Acuidade Visual

Introdução: A ambliopia é a principal causa de diminuição da acuidade visual em crianças. O diagnóstico e tratamento precoces são fundamentais para o sucesso terapêutico. A oclusão continua a ser o tratamento mais utilizado nesta patologia. Objectivos: Este estudo teve como objectivo a avaliação da estereopsia em crianças com ambliopia sob terapêutica oclusiva e a sua relação com a acuidade visual. Material e Métodos: Estudo prospectivo que incluiu 35 crianças com ambliopia, por anisometropia, estrabismo ou ambos, a fazer terapêutica oclusiva. Em cada consulta foi avaliada a melhor acuidade visual corrigida (MAVC) e a estereopsia para perto. Resultados: A idade média no início do estudo era de 6,17 anos (intervalo 3-9 anos) e o seguimento médio foi de 17 meses (intervalo 6-24 meses). Após tratamento com oclusão houve uma melhoria da MAVC média de 0,5 para 0,84 (p<0,001) e da estereopsia para perto de 1148 para 415 segundos de arco (p<0,001). Observou-se uma correlação linear significativa entre a melhoria da AV e da estereopsia (0,001visual está relacionada com uma melhoria da estereopsia.

Designing video lectures for MOOC

Educational videos differ from other teaching and learning technologies as they allow the benefit of using visual perception. Video lectures are not new to education, however with the use of innovative video technologies they can improve academic outcomes and extend the reach of education. They may offer extraordinary new experiences for higher education institutions (HEI). Through them lecturers can provide information and contents to students, and if used creatively, video lectures can become a powerful technological tool in education, inside and outside classrooms. Inside a classroom it can motivate students and improve topics’ debate and outside it is a good support for students’ self- learning. In some cases they can be used to work some subjects standing behind, but needed to support actual courses contents, that students do not remember (or were not even taught), opening an “in front to the past door” that backs students self-study. The student-educator dynamic is changing. Students are expecting exceptional instruction and educators are expecting students to be more and more well informed about subjects from online viewing.This article explores some of the potential benefits and challenges associated with the use of video lectures in the teaching and learning process at higher education. We will also discuss some thoughts and examples for the use of teaching materials to enhance student’s learning and try to understand how video can act as powerful and innovative to enlighten teaching and learning (note that unfortunately, sometimes, the opposite is happening).

Application of Visual-Inertial SLAM for 3D Mapping of Underground Environments

The underground scenarios are one of the most challenging environments for accurate and precise 3d mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS measurements acquired outside the tunnel. Results from the localization strategy are presented and analyzed.

Combining sparse and dense methods in 6D Visual Odometry

13th International Conference on Autonomous Robot Systems (Robotica), 2013, Lisboa

6D Visual Odometry with Dense Probabilistic Egomotion Estimation

Proceedings of the International Conference on Computer Vision Theory and Applications, 361-365, 2013, Barcelona, Spain

Real-Time Visual Ground-Truth System for Indoor Robotic Applications

The robotics community is concerned with the ability to infer and compare the results from researchers in areas such as vision perception and multi-robot cooperative behavior. To accomplish that task, this paper proposes a real-time indoor visual ground truth system capable of providing accuracy with at least more magnitude than the precision of the algorithm to be evaluated. A multi-camera architecture is proposed under the ROS (Robot Operating System) framework to estimate the 3D position of objects and the implementation and results were contextualized to the Robocup Middle Size League scenario.

Calibration Method for Underwater Visual Ground-Truth System

This work presents an automatic calibration method for a vision based external underwater ground-truth positioning system. These systems are a relevant tool in benchmarking and assessing the quality of research in underwater robotics applications. A stereo vision system can in suitable environments such as test tanks or in clear water conditions provide accurate position with low cost and flexible operation. In this work we present a two step extrinsic camera parameter calibration procedure in order to reduce the setup time and provide accurate results. The proposed method uses a planar homography decomposition in order to determine the relative camera poses and the determination of vanishing points of detected lines in the image to obtain the global pose of the stereo rig in the reference frame. This method was applied to our external vision based ground-truth at the INESC TEC/Robotics test tank. Results are presented in comparison with an precise calibration performed using points obtained from an accurate 3D LIDAR modelling of the environment.

Probabilistic Egomotion for Stereo Visual Odometry

We present a novel approach of Stereo Visual Odometry for vehicles equipped with calibrated stereo cameras. We combine a dense probabilistic 5D egomotion estimation method with a sparse keypoint based stereo approach to provide high quality estimates of vehicle’s angular and linear velocities. To validate our approach, we perform two sets of experiments with a well known benchmarking dataset. First, we assess the quality of the raw velocity estimates in comparison to classical pose estimation algorithms. Second, we added to our method’s instantaneous velocity estimates a Kalman Filter and compare its performance with a well known open source stereo Visual Odometry library. The presented results compare favorably with state-of-the-art approaches, mainly in the estimation of the angular velocities, where significant improvements are achieved.

Sensor Integration for Smart Cities Using Multi-Hop Networks

Smart Cities are designed to be living systems and turn urban dwellers life more comfortable and interactive by keeping them aware of what surrounds them, while leaving a greener footprint. The Future Cities Project [1] aims to create infrastructures for research in smart cities including a vehicular network, the BusNet, and an environmental sensor platform, the Urban Sense. Vehicles within the BusNet are equipped with On Board Units (OBUs) that offer free Wi-Fi to passengers and devices near the street. The Urban Sense platform is composed by a set of Data Collection Units (DCUs) that include a set of sensors measuring environmental parameters such as air pollution, meteorology and noise. The Urban Sense platform is expanding and receptive to add new sensors to the platform. The parnership with companies like TNL were made and the need to monitor garbage street containers emerged as air pollution prevention. If refuse collection companies know prior to the refuse collection which route is the best to collect the maximum amount of garbage with the shortest path, they can reduce costs and pollution levels are lower, leaving behind a greener footprint. This dissertation work arises in the need to monitor the garbage street containers and integrate these sensors into an Urban Sense DCU. Due to the remote locations of the garbage street containers, a network extension to the vehicular network had to be created. This dissertation work also focus on the Multi-hop network designed to extend the vehicular network coverage area to the remote garbage street containers. In locations where garbage street containers have access to the vehicular network, Roadside Units (RSUs) or Access Points (APs), the Multi-hop network serves has a redundant path to send the data collected from DCUs to the Urban Sense cloud database. To plan this highly dynamic network, the Wi-Fi Planner Tool was developed. This tool allowed taking measurements on the field that led to an optimized location of the Multi-hop network nodes with the use of radio propagation models. This tool also allowed rendering a temperature-map style overlay for Google Earth [2] application. For the DCU for garbage street containers the parner company provided the access to a HUB (device that communicates with the sensor inside the garbage containers). The Future Cities use the Raspberry pi as a platform for the DCUs. To collect the data from the HUB a RS485 to RS232 converter was used at the physical level and the Modbus protocol at the application level. To determine the location and status of the vehicles whinin the vehicular network a TCP Server was developed. This application was developed for the OBUs providing the vehicle Global Positioning System (GPS) location as well as information of when the vehicle is stopped, moving, on idle or even its slope. To implement the Multi-hop network on the field some scripts were developed such as pingLED and “shark”. These scripts helped upon node deployment on the field as well as to perform all the tests on the network. Two setups were implemented on the field, an urban setup was implemented for a Multi-hop network coverage survey and a sub-urban setup was implemented to test the Multi-hop network routing protocols, Optimized Link State Routing Protocol (OLSR) and Babel.