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

2D position system for a mobile robot in unstructured environments

Nowadays, several sensors and mechanisms are available to estimate a mobile robot trajectory and location with respect to its surroundings. Usually absolute positioning mechanisms are the most accurate, but they also are the most expensive ones, and require pre installed equipment in the environment. Therefore, a system capable of measuring its motion and location within the environment (relative positioning) has been a research goal since the beginning of autonomous vehicles. With the increasing of the computational performance, computer vision has become faster and, therefore, became possible to incorporate it in a mobile robot. In visual odometry feature based approaches, the model estimation requires absence of feature association outliers for an accurate motion. Outliers rejection is a delicate process considering there is always a trade-off between speed and reliability of the system. This dissertation proposes an indoor 2D position system using Visual Odometry. The mobile robot has a camera pointed to the ceiling, for image analysis. As requirements, the ceiling and the oor (where the robot moves) must be planes. In the literature, RANSAC is a widely used method for outlier rejection. However, it might be slow in critical circumstances. Therefore, it is proposed a new algorithm that accelerates RANSAC, maintaining its reliability. The algorithm, called FMBF, consists on comparing image texture patterns between pictures, preserving the most similar ones. There are several types of comparisons, with different computational cost and reliability. FMBF manages those comparisons in order to optimize the trade-off between speed and reliability.

Simulación de departamentos de urgencias empleando un modelo basado en agentes

Los servicios de salud son sistemas muy complejos, pero de alta importancia, especialmente en algunos momentos críticos, en todo el mundo. Los departamentos de urgencias pueden ser una de las áreas más dinámicas y cambiables de todos los servicios de salud y a la vez más vulnerables a dichos cambios. La mejora de esos departamentos se puede considerar uno de los grandes retos que tiene cualquier administrador de un hospital, y la simulación provee una manera de examinar este sistema tan complejo sin poner en peligro los pacientes que son atendidos. El objetivo de este trabajo ha sido el modelado de un departamento de urgencias y el desarrollo de un simulador que implementa este modelo con la finalidad de explorar el comportamiento y las características de dicho servicio de urgencias. El uso del simulador ofrece la posibilidad de visualizar el comportamiento del modelo con diferentes parámetros y servirá como núcleo de un sistema de ayuda a la toma de decisiones que pueda ser usado en departamentos de urgencias. El modelo se ha desarrollado con técnicas de modelado basado en agentes (ABM) que permiten crear modelos funcionalmente más próximos a la realidad que los modelos de colas o de dinámicas de sistemas, al permitir la inclusión de la singularidad que implica el modelado a nivel de las personas. Los agentes del modelo presentado, descritos internamente como máquinas de estados, representan a todo el personal del departamento de urgencias y los pacientes que usan este servicio. Un análisis del modelo a través de su implementación en el simulador muestra que el sistema se comporta de manera semejante a un departamento de urgencias real.

Evaluating the ability of habitat suitability models to predict species presences.

Models predicting species spatial distribution are increasingly applied to wildlife management issues, emphasising the need for reliable methods to evaluate the accuracy of their predictions. As many available datasets (e.g. museums, herbariums, atlas) do not provide reliable information about species absences, several presence-only based analyses have been developed. However, methods to evaluate the accuracy of their predictions are few and have never been validated. The aim of this paper is to compare existing and new presenceonly evaluators to usual presence/absence measures. We use a reliable, diverse, presence/absence dataset of 114 plant species to test how common presence/absence indices (Kappa, MaxKappa, AUC, adjusted D-2) compare to presenceonly measures (AVI, CVI, Boyce index) for evaluating generalised linear models (GLM). Moreover we propose a new, threshold-independent evaluator, which we call "continuous Boyce index". All indices were implemented in the B10MAPPER software. We show that the presence-only evaluators are fairly correlated (p > 0.7) to the presence/absence ones. The Boyce indices are closer to AUC than to MaxKappa and are fairly insensitive to species prevalence. In addition, the Boyce indices provide predicted-toexpected ratio curves that offer further insights into the model quality: robustness, habitat suitability resolution and deviation from randomness. This information helps reclassifying predicted maps into meaningful habitat suitability classes. The continuous Boyce index is thus both a complement to usual evaluation of presence/absence models and a reliable measure of presence-only based predictions.

Creació i transmissió de coneixement als clústers empresarials: un model de simulació

Projecte de recerca elaborat a partir d’una estada a l’Snider Entrepreneurial Research Center de la Wharton School de la University of Pennsilvanya y, EUA entre juliol i desembre del 2007. L’objectiu d’aquest projecte és estudiar la relació entre les estratègies de gestió del coneixement i les tecnologies de la informació i la comunicació (TIC) en l’evolució de les poblacions d’organitzacions i els seus efectes en els patrons industrials d’aglomeració espacial. Per a això s’adopta una aproximació fonamentada en la utilització d'un model basats en agents per a obtenir hipòtesis significatives i provables sobre l’evolució de les poblacions d’organitzacions al si de clústers geogràfics. El model de simulació incorpora les perspectives i supòsits d’un marc conceptual, l’Espai de la Informació o I-Space. Això permet una conceptualització basada en la informació de l’entorn econòmic que té en compte les seves dimensions espacials i temporals. Mitjançant els paràmetres del model es dóna la possibilitat d’assignar estratègies específiques de gestió del coneixement als diversos agents i de localitzar-los en una posició de l’espai físic. La simulació mostra com l'adopció d'estratègies diverses pel que fa a la gestió del coneixement influeix en l'evolució de les organitzacions i de la seva localització espacial, i que aquesta evolució es veu modificada pel desenvolupament de les TIC. A través de la modelització de dos casos ben coneguts de clústers geogràfics d’alta tecnologia, com són Silicon Valley a Califòrnia i la Route 128 als voltants de Boston, s’estudia la interrelació entre les estratègies de gestió del coneixement adoptades per les empreses i la seva tria de localització espacial, i també com això és afectat per l’evolució de les tecnologies de la informació i de la comunicació (TIC). Els resultats obtinguts generen una sèrie d’hipòtesis de rica potencialitat sobre l’impacte del desenvolupament de les TIC en la dinàmica d’aquests clusters geogràfics. Concretament, es troba que la estructuració del coneixement i l’aglomeració espacial co-evolucionen i que aquesta coevolució es veu significativament alterada pel desenvolupament de les TIC.

Sensitivity of predictive species distribution models to change in grain size

Predictive species distribution modelling (SDM) has become an essential tool in biodiversity conservation and management. The choice of grain size (resolution) of environmental layers used in modelling is one important factor that may affect predictions. We applied 10 distinct modelling techniques to presence-only data for 50 species in five different regions, to test whether: (1) a 10-fold coarsening of resolution affects predictive performance of SDMs, and (2) any observed effects are dependent on the type of region, modelling technique, or species considered. Results show that a 10 times change in grain size does not severely affect predictions from species distribution models. The overall trend is towards degradation of model performance, but improvement can also be observed. Changing grain size does not equally affect models across regions, techniques, and species types. The strongest effect is on regions and species types, with tree species in the data sets (regions) with highest locational accuracy being most affected. Changing grain size had little influence on the ranking of techniques: boosted regression trees remain best at both resolutions. The number of occurrences used for model training had an important effect, with larger sample sizes resulting in better models, which tended to be more sensitive to grain. Effect of grain change was only noticeable for models reaching sufficient performance and/or with initial data that have an intrinsic error smaller than the coarser grain size.

SLAM using an Imaging Sonar for Partially Structured Underwater Environments

In this paper we describe a system for underwater navigation with AUVs in partially structured environments, such as dams, ports or marine platforms. An imaging sonar is used to obtain information about the location of planar structures present in such environments. This information is incorporated into a feature-based SLAM algorithm in a two step process: (I) the full 360deg sonar scan is undistorted (to compensate for vehicle motion), thresholded and segmented to determine which measurements correspond to planar environment features and which should be ignored; and (2) SLAM proceeds once the data association is obtained: both the vehicle motion and the measurements whose correct association has been previously determined are incorporated in the SLAM algorithm. This two step delayed SLAM process allows to robustly determine the feature and vehicle locations in the presence of large amounts of spurious or unrelated measurements that might correspond to boats, rocks, etc. Preliminary experiments show the viability of the proposed approach

Underwater SLAM in a marina environment

This paper describes a navigation system for autonomous underwater vehicles (AUVs) in partially structured environments, such as dams, harbors, marinas or marine platforms. A mechanical scanning imaging sonar is used to obtain information about the location of planar structures present in such environments. A modified version of the Hough transform has been developed to extract line features, together with their uncertainty, from the continuous sonar dataflow. The information obtained is incorporated into a feature-based SLAM algorithm running an Extended Kalman Filter (EKF). Simultaneously, the AUV's position estimate is provided to the feature extraction algorithm to correct the distortions that the vehicle motion produces in the acoustic images. Experiments carried out in a marina located in the Costa Brava (Spain) with the Ictineu AUV show the viability of the proposed approach

Positioning an underwater vehicle through image mosaicking

Mosaics have been commonly used as visual maps for undersea exploration and navigation. The position and orientation of an underwater vehicle can be calculated by integrating the apparent motion of the images which form the mosaic. A feature-based mosaicking method is proposed in this paper. The creation of the mosaic is accomplished in four stages: feature selection and matching, detection of points describing the dominant motion, homography computation and mosaic construction. In this work we demonstrate that the use of color and textures as discriminative properties of the image can improve, to a large extent, the accuracy of the constructed mosaic. The system is able to provide 3D metric information concerning the vehicle motion using the knowledge of the intrinsic parameters of the camera while integrating the measurements of an ultrasonic sensor. The experimental results of real images have been tested on the GARBI underwater vehicle

MIGCLIM: Predicting plant distribution and dispersal in a changing climate

Many studies have forecasted the possible impact of climate change on plant distribution using models based on ecological niche theory. In their basic implementation, niche-based models do not constrain predictions by dispersal limitations. Hence, most niche-based modelling studies published so far have assumed dispersal to be either unlimited or null. However, depending on the rate of climatic change, the landscape fragmentation and the dispersal capabilities of individual species, these assumptions are likely to prove inaccurate, leading to under- or overestimation of future species distributions and yielding large uncertainty between these two extremes. As a result, the concepts of "potentially suitable" and "potentially colonisable" habitat are expected to differ significantly. To quantify to what extent these two concepts can differ, we developed MIGCLIM, a model simulating plant dispersal under climate change and landscape fragmentation scenarios. MIGCLIM implements various parameters, such as dispersal distance, increase in reproductive potential over time, barriers to dispersal or long distance dispersal. Several simulations were run for two virtual species in a study area of the western Swiss Alps, by varying dispersal distance and other parameters. Each simulation covered the hundred-year period 2001-2100 and three different IPCC-based temperature warming scenarios were considered. Our results indicate that: (i) using realistic parameter values, the future potential distributions generated using MIGCLIM can differ significantly (up to more than 95% decrease in colonized surface) from those that ignore dispersal; (ii) this divergence increases both with increasing climate warming and over longer time periods; (iii) the uncertainty associated with the warming scenario can be nearly as large as the one related to dispersal parameters; (iv) accounting for dispersal, even roughly, can importantly reduce uncertainty in projections.

Dugesia sicula (Platyhelminthes, Tricladida): the colonizing success of an asexual Planarian

Background Dugesia sicula is the only species of its genus not presenting an endemic or restricted distribution within the Mediterranean area. It mostly comprises fissiparous populations (asexual reproduction by body division and regeneration), most likely sexually sterile, and characterized by an extremely low genetic diversity interpreted as the consequence of a recent anthropic expansion. However, its fissiparous reproduction can result in an apparent lack of diversity within the species, since genetic variation within individuals can be as large as between them because most individuals within a population are clones. We have estimated haplotype and nucleotide diversity of cytochrome oxidase I within and among individuals along the species distribution of a broad sample of D. sicula, including asexual and the two only sexual populations known today; and predicted its potential distribution based on climatic variables. Our aim was to determine the centre of colonisation origin, whether the populations are recent, and whether the species is expanding. Results The species presents 3 most frequent haplotypes, differing in a maximum of 11 base pairs. As expected from their fissiparous mode of reproduction, in half of all the analysed localities many individuals have multiple heteroplasmic haplotypes. The distribution of haplotypes is not geographically structured; however, the distribution of haplotypes and heteroplasmic populations shows higher diversity in the central Mediterranean region. The potential distribution predicted by climatic variables based modelling shows a preference for coastal areas and fits well with the observed data. Conclusions The distribution and frequency of the most frequent haplotypes and the presence of heteroplasmic individuals allow us to gain an understanding of the recent history of the species, together with previous knowledge on its phylogenetic relationships and age: The species most probably originated in Africa and dispersed through the central Mediterranean. After one or multiple populations became triploid and fissiparous, the species colonized the Mediterranean basin, likely both by its own means and helped by human activities. Its present distribution practically fulfils its potential distribution as modelled with climatic variables. Its prevalence in coastal regions with higher water temperatures predicts a likely future expansion to northern and more interior areas following the increase in temperatures due to climate change.

Local Features in Image and Video Processing - Object Class Matching and Video Shot Detection

The usage of digital content, such as video clips and images, has increased dramatically during the last decade. Local image features have been applied increasingly in various image and video retrieval applications. This thesis evaluates local features and applies them to image and video processing tasks. The results of the study show that 1) the performance of different local feature detector and descriptor methods vary significantly in object class matching, 2) local features can be applied in image alignment with superior results against the state-of-the-art, 3) the local feature based shot boundary detection method produces promising results, and 4) the local feature based hierarchical video summarization method shows promising new new research direction. In conclusion, this thesis presents the local features as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.

Computational Market Dynamics of Virtual Economies

The last two decades have provided a vast opportunity to live and explore the compulsive imaginary world or virtual world through massively multiplayer online role-playing games (MMORPGs). MMORPG gives a wide range of opportunities to its users to participate with multi-players on the same platform, to communicate and to do real time actions. There is a virtual economy in these games which is largely player-driven. In-game currency provides its users to build up their Avatars, to buy or sell the necessary goods to play, survive in the games and so on. As a part of virtual economies generated through EVE Online, this thesis mainly focuses on how the prices of the minerals in EVE Online behave by applying the Jabłonska- Capasso-Morale (JCM) mathematical simulation model. It is to verify up to what degree the model can reproduce the virtual economy behavior. The model is applied to buy and sell prices of two minerals namely, isogen and morphite. The simulation results demonstrate that JCM model ts reasonably well to the mineral prices, which lets us conclude that virtual economies behave similarly to the real ones.

Alignment by Maximization of Mutual Information

A new information-theoretic approach is presented for finding the pose of an object in an image. The technique does not require information about the surface properties of the object, besides its shape, and is robust with respect to variations of illumination. In our derivation, few assumptions are made about the nature of the imaging process. As a result the algorithms are quite general and can foreseeably be used in a wide variety of imaging situations. Experiments are presented that demonstrate the approach registering magnetic resonance (MR) images with computed tomography (CT) images, aligning a complex 3D object model to real scenes including clutter and occlusion, tracking a human head in a video sequence and aligning a view-based 2D object model to real images. The method is based on a formulation of the mutual information between the model and the image called EMMA. As applied here the technique is intensity-based, rather than feature-based. It works well in domains where edge or gradient-magnitude based methods have difficulty, yet it is more robust than traditional correlation. Additionally, it has an efficient implementation that is based on stochastic approximation. Finally, we will describe a number of additional real-world applications that can be solved efficiently and reliably using EMMA. EMMA can be used in machine learning to find maximally informative projections of high-dimensional data. EMMA can also be used to detect and correct corruption in magnetic resonance images (MRI).