People and object tracking for video annotation

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Sistema de detecção de fogo e detecção e seguimento de objectos

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Autonomous behaviors for an unmanned mini-aerial vehicle

This thesis aims at addressing the development of autonomous behaviors, for search and exploration with a mini-UAV (Unmanned Aerial Vehicle), or also called MAV (Mini Aerial Vehicle) prototype, in order to gather information in rescue scenarios. The platform used in this work is a four rotor helicopter, known as quad-rotor from the German company Ascending Technologies GmbH, which is later assembled with a on-board processing unit (i.e. a tiny light weight computer) and a on-board sensor suite (i.e. 2D-LIDAR and Ultrasonic Sonar). This work can be divided into two phases. In the first phase an Indoor Position Tracking system was settled in order to obtain the Cartesian coordinates (i.e. X, Y, Z) and orientation (i.e.heading) which provides the relative position and orientation of the platform. The second phase was the design and implementation of medium/high level controllers on each command input in order to autonomously control the aircraft position, which is the first step towards an autonomous hovering flight, and any autonomous behavior (e.g. Landing, Object avoidance, Follow the wall). The main work is carried out in the Laboratory ”Intelligent Systems for Emergencies and Civil Defense”, in collaboration with ”Dipartimento di Informatica e Sistemistica” of Sapienza Univ. of Rome and ”Istituto Superiore Antincendi” of the Italian Firemen Department.

A type system for access control in an object-oriented language

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

Analysis of support for modularity in object teams based on design patterns

Dissertação de Mestrado em Engenharia Informática

Land use / land cover change detection: an object oriented approach, Münster, Germany

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Genomic and transcriptomic features of Chlamydia trachomatis. Tracking the basis for the ecological success

Dissertation presented to obtain a Ph.D degree in Biology, speciality in Molecular Genetics, by Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

A learning approach to swarm-based path detection and tracking

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Automated segmentation, tracking and evaluation of bacteria in microscopy images

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Weekly tracking of stability of the flow of conversations into the subprocesses of the Last Planner System

21st Annual Conference of the International Group for Lean Construction – IGLC 21 – Fortaleza, Brazil

Um estudo de performance de uma ferramenta de Object/Relational Mapping

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Video interaction using pen-based technology

Dissertação para obtenção do Grau de Doutor em Informática

Amorphous silicon e 3D sensors applied to object detection

Nowadays, existing 3D scanning cameras and microscopes in the market use digital or discrete sensors, such as CCDs or CMOS for object detection applications. However, these combined systems are not fast enough for some application scenarios since they require large data processing resources and can be cumbersome. Thereby, there is a clear interest in exploring the possibilities and performances of analogue sensors such as arrays of position sensitive detectors with the final goal of integrating them in 3D scanning cameras or microscopes for object detection purposes. The work performed in this thesis deals with the implementation of prototype systems in order to explore the application of object detection using amorphous silicon position sensors of 32 and 128 lines which were produced in the clean room at CENIMAT-CEMOP. During the first phase of this work, the fabrication and the study of the static and dynamic specifications of the sensors as well as their conditioning in relation to the existing scientific and technological knowledge became a starting point. Subsequently, relevant data acquisition and suitable signal processing electronics were assembled. Various prototypes were developed for the 32 and 128 array PSD sensors. Appropriate optical solutions were integrated to work together with the constructed prototypes, allowing the required experiments to be carried out and allowing the achievement of the results presented in this thesis. All control, data acquisition and 3D rendering platform software was implemented for the existing systems. All these components were combined together to form several integrated systems for the 32 and 128 line PSD 3D sensors. The performance of the 32 PSD array sensor and system was evaluated for machine vision applications such as for example 3D object rendering as well as for microscopy applications such as for example micro object movement detection. Trials were also performed involving the 128 array PSD sensor systems. Sensor channel non-linearities of approximately 4 to 7% were obtained. Overall results obtained show the possibility of using a linear array of 32/128 1D line sensors based on the amorphous silicon technology to render 3D profiles of objects. The system and setup presented allows 3D rendering at high speeds and at high frame rates. The minimum detail or gap that can be detected by the sensor system is approximately 350 μm when using this current setup. It is also possible to render an object in 3D within a scanning angle range of 15º to 85º and identify its real height as a function of the scanning angle and the image displacement distance on the sensor. Simple and not so simple objects, such as a rubber and a plastic fork, can be rendered in 3D properly and accurately also at high resolution, using this sensor and system platform. The nip structure sensor system can detect primary and even derived colors of objects by a proper adjustment of the integration time of the system and by combining white, red, green and blue (RGB) light sources. A mean colorimetric error of 25.7 was obtained. It is also possible to detect the movement of micrometer objects using the 32 PSD sensor system. This kind of setup offers the possibility to detect if a micro object is moving, what are its dimensions and what is its position in two dimensions, even at high speeds. Results show a non-linearity of about 3% and a spatial resolution of < 2µm.

Tracking error of exchange-traded funds: Evidence from the UK

This paper is mainly concerned with the tracking accuracy of Exchange Traded Funds (ETFs) listed on the London Stock Exchange (LSE) but also evaluates their performance and pricing efficiency. The findings show that ETFs offer virtually the same return but exhibit higher volatility than their benchmark. It seems that the pricing efficiency, which should come from the creation and redemption process, does not fully hold as equity ETFs show consistent price premiums. The tracking error of the funds is generally small and is decreasing over time. The risk of the ETF, daily price volatility and the total expense ratio explain a large part of the tracking error. Trading volume, fund size, bid-ask spread and average price premium or discount did not have an impact on the tracking error. Finally, it is concluded that market volatility and the tracking error are positively correlated.

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.