Global localization with non-quantized local image features

In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.

Reafirmar a Identidade cultural local: o património cultural imaterial local como recurso

Dissertação conducente à obtenção do grau de Mestre em Educação Social e Intervenção Comunitária, sob orientação do Professor Doutor Luís Manuel Costa Moreno

O património local como recurso para o desenvolvimento de competências essenciais da história no 1.º ciclo

Relatório de Estágio apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ensino do 1.º e do 2.º Ciclo do Ensino Básico

GLODS: Global and Local Optimization using Direct Search

Locating and identifying points as global minimizers is, in general, a hard and time-consuming task. Difficulties increase in the impossibility of using the derivatives of the functions defining the problem. In this work, we propose a new class of methods suited for global derivative-free constrained optimization. Using direct search of directional type, the algorithm alternates between a search step, where potentially good regions are located, and a poll step where the previously located promising regions are explored. This exploitation is made through the launching of several instances of directional direct searches, one in each of the regions of interest. Differently from a simple multistart strategy, direct searches will merge when sufficiently close. The goal is to end with as many direct searches as the number of local minimizers, which would easily allow locating the global extreme value. We describe the algorithmic structure considered, present the corresponding convergence analysis and report numerical results, showing that the proposed method is competitive with currently commonly used global derivative-free optimization solvers.

Planning smart cities using wireless low energy monitoring systems

Thesis to obtain the Master Degree in Electronics and Telecommunications Engineering

Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.

Implementação de um sistema de gestão municipal com recurso a sistemas de informação geográfica

Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Vias de Comunicação e Transportes

The insular shelves of the Faial-Pico Ridge (Azores archipelago): a morphological record of its evolution

Shelves surrounding reefless volcanic ocean islands are formed by surf erosion of their slopes during changing sea levels. Posterosional lava flows, if abundant, can cross the coastal cliffs and fill partially or completely the accommodation space left by erosion. In this study, multibeam bathymetry, high-resolution seismic reflection profiles, and sediment samples are used to characterize the morphology of the insular shelves adjacent to Pico Island. The data show offshore fresh lava flow morphologies, as well as an irregular basement beneath shelf sedimentary bodies and reduced shelf width adjacent to older volcanic edifices in Pico. These observations suggest that these shelves have been significantly filled by volcanic progradation and can thus be classified as rejuvenated. Despite the general volcanic infilling of the shelves around Pico, most of their edges are below the depth of the Last Glacial Maximum, revealing that at least parts of the island have subsided after the shelves formed by surf erosion. Prograding lava deltas reached the shelf edge in some areas triggering small slope failures, locally decreasing the shelf width and depth of their edges. These areas can represent a significant risk for the local population; hence, their identification can be useful for hazard assessment and contribute to wiser land use planning. Shelf and subaerial geomorphology, magnetic anomalies and crustal structure data of the two islands were also interpreted to reconstruct the long-term combined onshore and offshore evolution of the Faial-Pico ridge. The subaerial emergence of this ridge is apparently older than previously thought, i.e., before approximate to 850 ka.