14 research outputs found

    MAP3D: An explorative approach for automatic mapping of real-world eye-tracking data on a virtual 3D model

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    Mobile eye tracking helps to investigate real-world settings, in which participants can move freely. This enhances the studies’ ecological validity but poses challenges for the analysis. Often, the 3D stimulus is reduced to a 2D image (reference view) and the fixations are manually mapped to this 2D image. This leads to a loss of information about the three-dimensionality of the stimulus. Using several reference images, from different perspectives, poses new problems, in particular concerning the mapping of fixations in the transition areas between two reference views. A newly developed approach (MAP3D) is presented that enables generating a 3D model and automatic mapping of fixations to this virtual 3D model of the stimulus. This avoids problems with the reduction to a 2D reference image and with transitions between images. The x, y and z coordinates of the fixations are available as a point cloud and as .csv output. First exploratory application and evaluation tests are promising: MAP3D offers innovative ways of post-hoc mapping fixation data on 3D stimuli with open-source software and thus provides cost-efficient new avenues for research

    Estimation of heartbeat peak locations and heartbeat rate from facial video

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    MAP3D: An explorative approach for automatic mapping of real-world eye-tracking data on a virtual 3D model

    Get PDF
    Mobile eye tracking helps to investigate real-world settings, in which participants can move freely. This enhances the studies’ ecological validity but poses challenges for the analysis. Often, the 3D stimulus is reduced to a 2D image (reference view) and the fixations are manually mapped to this 2D image. This leads to a loss of information about the three-dimensionality of the stimulus. Using several reference images, from different perspectives, poses new problems, in particular concerning the mapping of fixations in the transition areas between two reference views. A newly developed approach (MAP3D) is presented that enables generating a 3D model and automatic mapping of fixations to this virtual 3D model of the stimulus. This avoids problems with the reduction to a 2D reference image and with transitions between images. The x, y and z coordinates of the fixations are available as a point cloud and as .csv output. First exploratory application and evaluation tests are promising: MAP3D offers innovative ways of post-hoc mapping fixation data on 3D stimuli with open-source software and thus provides cost-efficient new avenues for research

    Modelling and recognition of protein contact networks by multiple kernel learning and dissimilarity representations

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    Multiple kernel learning is a paradigm which employs a properly constructed chain of kernel functions able to simultaneously analyse different data or different representations of the same data. In this paper, we propose an hybrid classification system based on a linear combination of multiple kernels defined over multiple dissimilarity spaces. The core of the training procedure is the joint optimisation of kernel weights and representatives selection in the dissimilarity spaces. This equips the system with a two-fold knowledge discovery phase: by analysing the weights, it is possible to check which representations are more suitable for solving the classification problem, whereas the pivotal patterns selected as representatives can give further insights on the modelled system, possibly with the help of field-experts. The proposed classification system is tested on real proteomic data in order to predict proteins' functional role starting from their folded structure: specifically, a set of eight representations are drawn from the graph-based protein folded description. The proposed multiple kernel-based system has also been benchmarked against a clustering-based classification system also able to exploit multiple dissimilarities simultaneously. Computational results show remarkable classification capabilities and the knowledge discovery analysis is in line with current biological knowledge, suggesting the reliability of the proposed system

    Télédétection spatiale de dépôts d'avalanche pour le suivi de zones à risque avalancheux

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    La surveillance du manteau neigeux, la prévision de son évolution et l'estimation du risque d'avalanche qui en découle font partie des missions de Météo-France. L'hétérogénéité des montagnes induite par le relief rend la prévision nivo-météorologique de ces territoires particulièrement difficile. A cela s'ajoute une forte demande sociétale de disposer de prévisions fiables de l'enneigement et du risque d'avalanche avec un niveau d'exigence sans cesse en accroissement tant sur la qualité des prévisions que sur leur forme et leur étendue géographique. La mise à disposition aux prévisionnistes nivologues et aux autres acteurs de montagne d'observation systématique sur l'activité avalancheuse permettrait une meilleure qualification des situations prévues par rapport aux événements passés et contribuerait à l'amélioration de la gestion du risque avalancheux. La localisation et l'estimation de taille des dépôts d'avalanches sont d'une grande importance pour les études de stabilité du manteau neigeux. Les avancées en matière de télédétection spatiale offrent la possibilité aux chercheurs et acteurs de montagne de suivre au plus près l'évolution du manteau neigeux. Dans cette thèse, nous exploitons les données d'observations satellitaires de Sentinel-1 couvrant l'intégralité des Alpes pour détecter les zones de débris avalancheux et pour suivre l'évolution de l'activité avalancheuse à l'échelle d'une région d'intérêt. Une méthode est développée permettant de détecter automatiquement les zones de débris d'avalanche de neige en utilisant une technique de segmentation novatrices des images Sentinel-1. Plusieurs autres développements algorithmiques sont menés pour améliorer les détections impliquant des méthodes de filtrage de fausses détection et de classification pour passer d'un ensemble de pixels avalancheux à un événement avalancheux. Les estimations de débris sont étudiées et leurs dépendances selon la direction de l'orbite, les caractéristiques du terrain (pente, altitude, orientation) examinées. La méthode de détection est également évaluée avec succès à l'aide d'une base de données indépendante issues d’identifications de débris d’avalanches sur une image optique de haute résolution. Par la suite, nous dérivons des indicateurs spatialisés à l'échelle des massifs de l'activité avalancheuses. Il s'agit de lignes de débris d'avalanches estimées par pente et par bandes d'altitudes. Ces indicateurs sont comparés à des données d'observations in-situ. Ce travail de thèse permet le développement de nouveaux produits à valeur ajoutée et est l'occasion d'initier une réflexion sur les besoins pour la prévision du risque d'avalanche et notamment le besoin de disposer d'indicateurs « synthétisables » sur des fenêtres temporelles d'intérêts (hebdomadaire, mensuelle, saisonnière) à des échelles allant de l'échelle locale (de l'événement) à l'échelle du massif

    In Search of the Culprit

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    Despite poststructuralist rejections of the idea of a singular author-genius, the question of a textual archetype that can be assigned to a named author is still a common scholarly phantasm. This volume sets new standards by applying current theoretical approaches to the question of concepts of authorship in medieval and early modern literature. The basic thesis is that authorship is a narratological function rather than an extra-textual entity

    Online Personalization in Exploratory Search

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    Modern society produces vast amounts of digital data related to multiple domains of our lives. We produce data in our free time when browsing the net or taking photos with various personal devices, such as phones or ipads. Businesses and governments also gather a lot of information related to our interests, habits or otherwise personal information (legal status, health data, etc.). The amount of data produced is growning too large for us to be handled manually, and so to assist the user, specialized information retrieval systems have been developed to allow efficient perusal of different types of data. Unfortunately, as using such systems often requires expert understanding of the domain in question, many users get lost in their attempt to navigate the search space. This problem will only be exacerbated in the future, as the amount of data keeps growing, giving us less time to learn about the domains involved. Exploratory search is a field of research that studies user behaviour in situations, where users have little familiarity with the search domain, or have not yet decided exactly what their search goal is. Situations such as these arise when the user wishes to explore what is available, or is otherwise synthesizing or investigating the data. To assist the user in exploratory search and in finding relevant information, various methodologies may be employed, such as user modeling techniques or novel interfaces and data visualization techniques. This thesis presents exploratory search techniques for online personalization and feature representations that allow efficient perusal of unknown datasets. These methods are showcased in two different search environments. First, we present a search engine for scientific document retrieval, which takes the user's knowledge level into account in order to provide the user with more or less diverse search results. The second search environment aims at supporting the user when browsing through a dataset of unannotated images. Overall, the research presented here describes a number of techniques based on reinforcement learning and neural networks that, compared to traditional search engines, can provide better support for users who are unsure of the final goal of their search or who cannot easily formulate their search needs.Moderni yhteiskunta tuottaa suuria määriä digitaalista dataa liittyen elämämme eri osa-alueisiin. Tuotamme tätä dataa vapaa-ajallamme kun käymme internetissä, tai tuotamme moninaista multimediaa eri älylaitteillamme. Tämä näkyy vahvasti myös yritysten liiketoiminnassa ja valtioiden hallinnassa, missä erilaisten toimintojen seurantaa kirjataan digitaalisesti, kuten laillisen informaation, terveysdatan ja henkilökohtaisen datan muodossa. Tuotetun datan määrä on kasvamassa liian suureksi yksittäisten ihmisten käsiteltäväksi, ja täten järjestelmiä mitkä automatisoivat hakuprosessia tuotetaan enenevässä määrin. Valitettavasti, useat näistä järjestelmistä vaativat asiantuntemusta annetulta alalta, minkä takia käyttäjät eksyvät helposti hakuavaruuteen. Exploratiivinen haku on tieteenala joka tutkii käyttäjän käyttäytyymistä tilanteissa, missä heillä on vähän tuntemusta alalta, tai he eivät ole vielä päättäneet mikä on heidän hakunsa päämäärä. Tällaiset tilanteet syntyvät kun käyttäjä haluaa kartoittaa saatavilla olevaa aineistoa, tai muuten syntetisoida tai tutkia kyseistä dataa. Oleellisen tiedon löytämiseksi exploratiivinen haku hyödyntää erilaisia menetelmiä, kuten käyttäjän mallintamista, erikoisia käyttöliittymiä tai datan visualisointimenetelmiä. Tämä kirja esittelee exploratiivisen haun menetelmiä ajantasaiseen personalisointiin ja piirrerepresentaatioihin, mitkä mahdollistavat käyttäjälle entuudestaan tuntemattomien tietokantojen tehokkaan käsittelyn. Nämä menetelmät esitellään kahden hakujärjestelmän yhteydessä. Ensiksi, esittelemme hakukoneen tieteellisille artikkeleille, mikä ottaa käyttäjän tietotason huomioon kun hakutuloksia esitellään. Jälkimmäinen hakukone mahdollistaa annotoimattomien kuvien tehokkaan selailun. Kokonaisuudessaan, tämä kirja kertoo useasta tutkimus- ja järjestelmämenetelmästä, mitkä, verrattuna perinteisiin hakukoneisiin, tukevat epävarman käyttäjän hakuprosessia tuntemattomassa ympäristössä paremmin

    In Search of the Culprit

    Get PDF
    Despite poststructuralist rejections of the idea of a singular author-genius, the question of a textual archetype that can be assigned to a named author is still a common scholarly phantasm. This volume sets new standards by applying current theoretical approaches to the question of concepts of authorship in medieval and early modern literature. The basic thesis is that authorship is a narratological function rather than an extra-textual entity

    Norse shielings in Scotland: an interdisciplinary study of setr/sætr and ærgi-names

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    This is a study of the Old Norse (hereafter abbreviated to ON) setr/sætr and ærgi place-names in areas of Scandinavian settlement in Scotland. The elements setr/sætr and ærgi all have a general meaning of a place for summer grazing in the hills, referred to in Scotland as a shieling. However, the related terms setr and sætr, are employed as shielings names in Norway and are indistinguishable from each other in Britain. It is only in areas of Scandinavian settlement in Britain and the Faroes that ærgi is found to signify a shieling site. The element ærgi was adopted as a loanword from either, the Scottish Gaelic àirigh or Irish áirge, both of which can also have the meaning of a shieling. What is unusual about this adoption is it is rare for a more prestigious speech community (ON in this instance) to adopt a word from, what is believed to have been, a less prestigious language at the time (Gaelic). Various scholars have looked at this question, but none have adequately explained the reason for the adoption. Much of the previous research has relied on comparisons of local farming systems that were recorded many centuries after the Viking Age. Farming techniques from the fifteenth to twentieth century are unlikely to adequately represent the agricultural situation in the Viking Age due to different social imperatives. The overall question I want to answer in this thesis, is why Scandinavian settlers in Scotland adopted ærgi, when they already had corresponding ON terms for a shieling. The distribution of ON settlement names is one of the main pieces of evidence to prove Scandinavian settlement in Scotland during this period. This is especially true of secondary settlements, such as shielings, which rarely feature in early documentation. The language shift to either Gaelic or Scots-English is likely to have led to the loss of many ON place-names, but will also have fossilised some names in the landscape. The location of these settlement names can give an understanding of how Scandinavian settlers utilised the landscape and highlight differences in the use of different shieling names. This thesis is interdisciplinary in nature, but one based on cultural and historical geography. The first element of the study is to understand why shielings developed in Scandinavian society and if there are identifiable environmental factors behind their location. Studies in Norway suggest shielings developed as a response to environmental constraints to agriculture and social pressures to produce a surplus. A locational study of shielings in areas that were the likely origin of Viking settlers in Norway, highlighted seven key locations for shielings. These locational factors were then compared to setr/sætr-names in Scotland. The locations were broadly similar to Norwegian shielings, however, Scottish setr/sætr-names were more likely to be situated in slightly more fertile locations than Norwegian examples studied. A comparison of Scottish setr/sætr-names with ærgi-names also revealed the latter to be more likely found on even richer grazing land. The conclusion being, setr/sætr had a more general meaning of a place for summer grazing, whereas, ærgi was specifically linked to richer soils and richer grazing land. This link may relate to an intensive dairy economy, something which is known from contemporary documentary sources from the Gaelic world, but has not been proven in pre-Viking Age Norway
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