F-formation Detection: Individuating Free-standing Conversational Groups in Images

Detection of groups of interacting people is a very interesting and useful task in many modern technologies, with application fields spanning from video-surveillance to social robotics. In this paper we first furnish a rigorous definition of group considering the background of the social sciences: this allows us to specify many kinds of group, so far neglected in the Computer Vision literature. On top of this taxonomy, we present a detailed state of the art on the group detection algorithms. Then, as a main contribution, we present a brand new method for the automatic detection of groups in still images, which is based on a graph-cuts framework for clustering individuals; in particular we are able to codify in a computational sense the sociological definition of F-formation, that is very useful to encode a group having only proxemic information: position and orientation of people. We call the proposed method Graph-Cuts for F-formation (GCFF). We show how GCFF definitely outperforms all the state of the art methods in terms of different accuracy measures (some of them are brand new), demonstrating also a strong robustness to noise and versatility in recognizing groups of various cardinality.Comment: 32 pages, submitted to PLOS On

Optimized Path Planning for USVs under Ocean Currents

The proposed work focuses on the path planning for Unmanned Surface Vehicles (USVs) in the ocean enviroment, taking into account various spatiotemporal factors such as ocean currents and other energy consumption factors. The paper proposes the use of Gaussian Process Motion Planning (GPMP2), a Bayesian optimization method that has shown promising results in continuous and nonlinear path planning algorithms. The proposed work improves GPMP2 by incorporating a new spatiotemporal factor for tracking and predicting ocean currents using a spatiotemporal Bayesian inference. The algorithm is applied to the USV path planning and is shown to optimize for smoothness, obstacle avoidance, and ocean currents in a challenging environment. The work is relevant for practical applications in ocean scenarios where an optimal path planning for USVs is essential for minimizing costs and optimizing performance.Comment: 9 pages and 7 figures, submitted for IEEE Transactions on Man, systems ,and Cybernetic

Visual attention and swarm cognition for off-road robots

Tese de doutoramento, Informática (Engenharia Informática), Universidade de Lisboa, Faculdade de Ciências, 2011Esta tese aborda o problema da modelação de atenção visual no contexto de robôs autónomos todo-o-terreno. O objectivo de utilizar mecanismos de atenção visual é o de focar a percepção nos aspectos do ambiente mais relevantes à tarefa do robô. Esta tese mostra que, na detecção de obstáculos e de trilhos, esta capacidade promove robustez e parcimónia computacional. Estas são características chave para a rapidez e eficiência dos robôs todo-o-terreno. Um dos maiores desafios na modelação de atenção visual advém da necessidade de gerir o compromisso velocidade-precisão na presença de variações de contexto ou de tarefa. Esta tese mostra que este compromisso é resolvido se o processo de atenção visual for modelado como um processo auto-organizado, cuja operação é modulada pelo módulo de selecção de acção, responsável pelo controlo do robô. Ao fechar a malha entre o processo de selecção de acção e o de percepção, o último é capaz de operar apenas onde é necessário, antecipando as acções do robô. Para fornecer atenção visual com propriedades auto-organizadas, este trabalho obtém inspiração da Natureza. Concretamente, os mecanismos responsáveis pela capacidade que as formigas guerreiras têm de procurar alimento de forma auto-organizada, são usados como metáfora na resolução da tarefa de procurar, também de forma auto-organizada, obstáculos e trilhos no campo visual do robô. A solução proposta nesta tese é a de colocar vários focos de atenção encoberta a operar como um enxame, através de interacções baseadas em feromona. Este trabalho representa a primeira realização corporizada de cognição de enxame. Este é um novo campo de investigação que procura descobrir os princípios básicos da cognição, inspeccionando as propriedades auto-organizadas da inteligência colectiva exibida pelos insectos sociais. Logo, esta tese contribui para a robótica como disciplina de engenharia e para a robótica como disciplina de modelação, capaz de suportar o estudo do comportamento adaptável.Esta tese aborda o problema da modelação de atenção visual no contexto de robôs autónomos todo-o-terreno. O objectivo de utilizar mecanismos de atenção visual é o de focar a percepção nos aspectos do ambiente mais relevantes à tarefa do robô. Esta tese mostra que, na detecção de obstáculos e de trilhos, esta capacidade promove robustez e parcimónia computacional. Estas são características chave para a rapidez e eficiência dos robôs todo-o-terreno. Um dos maiores desafios na modelação de atenção visual advém da necessidade de gerir o compromisso velocidade-precisão na presença de variações de contexto ou de tarefa. Esta tese mostra que este compromisso é resolvido se o processo de atenção visual for modelado como um processo auto-organizado, cuja operação é modulada pelo módulo de selecção de acção, responsável pelo controlo do robô. Ao fechar a malha entre o processo de selecção de acção e o de percepção, o último é capaz de operar apenas onde é necessário, antecipando as acções do robô. Para fornecer atenção visual com propriedades auto-organizadas, este trabalho obtém inspi- ração da Natureza. Concretamente, os mecanismos responsáveis pela capacidade que as formi- gas guerreiras têm de procurar alimento de forma auto-organizada, são usados como metáfora na resolução da tarefa de procurar, também de forma auto-organizada, obstáculos e trilhos no campo visual do robô. A solução proposta nesta tese é a de colocar vários focos de atenção encoberta a operar como um enxame, através de interacções baseadas em feromona. Este trabalho representa a primeira realização corporizada de cognição de enxame. Este é um novo campo de investigação que procura descobrir os princípios básicos da cognição, ins- peccionando as propriedades auto-organizadas da inteligência colectiva exibida pelos insectos sociais. Logo, esta tese contribui para a robótica como disciplina de engenharia e para a robótica como disciplina de modelação, capaz de suportar o estudo do comportamento adaptável.Fundação para a Ciência e a Tecnologia (FCT,SFRH/BD/27305/2006); Laboratory of Agent Modelling (LabMag

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

Acoustic Speaker Localization with Strong Reverberation and Adaptive Feature Filtering with a Bayes RFS Framework

The thesis investigates the challenges of speaker localization in presence of strong reverberation, multi-speaker tracking, and multi-feature multi-speaker state filtering, using sound recordings from microphones. Novel reverberation-robust speaker localization algorithms are derived from the signal and room acoustics models. A multi-speaker tracking filter and a multi-feature multi-speaker state filter are developed based upon the generalized labeled multi-Bernoulli random finite set framework. Experiments and comparative studies have verified and demonstrated the benefits of the proposed methods

An Evolutionary Approach to Multistage Portfolio Optimization

Portfolio optimization is an important problem in quantitative finance due to its application in asset management and corporate financial decision making. This involves quantitatively selecting the optimal portfolio for an investor given their asset return distribution assumptions, investment objectives and constraints. Analytical portfolio optimization methods suffer from limitations in terms of the problem specification and modelling assumptions that can be used. Therefore, a heuristic approach is taken where Monte Carlo simulations generate the investment scenarios and' a problem specific evolutionary algorithm is used to find the optimal portfolio asset allocations. Asset allocation is known to be the most important determinant of a portfolio's investment performance and also affects its risk/return characteristics. The inclusion of equity options in an equity portfolio should enable an investor to improve their efficient frontier due to options having a nonlinear payoff. Therefore, a research area of significant importance to equity investors, in which little research has been carried out, is the optimal asset allocation in equity options for an equity investor. A purpose of my thesis is to carry out an original analysis of the impact of allowing the purchase of put options and/or sale of call options for an equity investor. An investigation is also carried out into the effect ofchanging the investor's risk measure on the optimal asset allocation. A dynamic investment strategy obtained through multistage portfolio optimization has the potential to result in a superior investment strategy to that obtained from a single period portfolio optimization. Therefore, a novel analysis of the degree of the benefits of a dynamic investment strategy for an equity portfolio is performed. In particular, the ability of a dynamic investment strategy to mimic the effects ofthe inclusion ofequity options in an equity portfolio is investigated. The portfolio optimization problem is solved using evolutionary algorithms, due to their ability incorporate methods from a wide range of heuristic algorithms. Initially, it is shown how the problem specific parts ofmy evolutionary algorithm have been designed to solve my original portfolio optimization problem. Due to developments in evolutionary algorithms and the variety of design structures possible, a purpose of my thesis is to investigate the suitability of alternative algorithm design structures. A comparison is made of the performance of two existing algorithms, firstly the single objective stepping stone island model, where each island represents a different risk aversion parameter, and secondly the multi-objective Non-Dominated Sorting Genetic Algorithm2. Innovative hybrids of these algorithms which also incorporate features from multi-objective evolutionary algorithms, multiple population models and local search heuristics are then proposed. . A novel way is developed for solving the portfolio optimization by dividing my problem solution into two parts and then applying a multi-objective cooperative coevolution evolutionary algorithm. The first solution part consists of the asset allocation weights within the equity portfolio while the second solution part consists 'ofthe asset allocation weights within the equity options and the asset allocation weights between the different asset classes. An original portfolio optimization multiobjective evolutionary algorithm that uses an island model to represent different risk measures is also proposed.Imperial Users onl