RAUTERBERG , Matthias

In this work, the problems of knowledge acquisition and information processing are explored in relation to the definitions of concepts and conceptual processing, and their implications for artificial agents. The discussion focuses on views of cognition as a dynamic property in which the world is actively represented in grounded mental states...

This paper presents a Learning Analytics approach for understanding the learning behavior of students while interacting with Technology Enhanced Learning tools. In this work we show that it is possible to gain insight into the learning processes of students from their interaction data. We base our study on data collected through six laboratory...

Simulation of crowd behaviors is a widely discussed topic for over a decade for computer games, architecture and entertainment. The most important thing is that agents should execute the human like behaviors in real life scenarios. This situation becomes very complex with dense crowds. Our proposed Realistic Behavior Agent Simulation (RBAS)...

Learning Analytics (LA) has a major interest in exploring and understanding the learning process of humans and, for this purpose, benefits from both Cognitive Science, which studies how humans learn, and Machine Learning, which studies how algorithms learn from data. Usually, Machine Learning is exploited as a tool for analyzing data coming...

Approximately, one-third to half of all food produced globally is wasted. In developed countries, roughly up to half of this food waste comes from consumers. In response to this, the UN has set goals to raise consumer awareness and reduce food waste by 50% before 2030. Our objective is to evaluate how emerging technologies could improve...

Inspired by Gustave Lebon's idea of crowds as single-minded entities, we present a novel approach to describe the behavior of a crowd as a single entity, based on the global movement of the entire aggregate of people conforming the crowd. The present work significantly differs from existing literature where the behavior of single individuals...

This tutorial aims to introduce the benefits of applying a service-oriented architecture (SOA) approach to serious games developers. For that end, we propose a hands-on session in which we will provide information on state-of-the-art services for serious games and guide developers in rethinking one of their existing games or game ideas using...

In Machine Learning (ML), the learning process of an algorithm given a set of evidences is studied via complexity measures. The way towards using ML complexity measures in the Human Learning (HL) domain has been paved by a previous study, which introduced Human Rademacher Complexity (HRC): in this work, we introduce Human Algorithmic Stability...

The growing interest in recent years towards Learning Analytics (LA) and Educational Data Mining (EDM) has enabled novel approaches and advancements in educational settings. The wide variety of research and practice in this context has enforced important possibilities and applications from adaptation and personalization of Technology Enhanced...

The automatic collection of data concerning the interaction between students and Technology Enhanced Learning (TEL) systems has become increasingly common. Such data availability has led to applications of Learning Analytics (LA) techniques, characterized by the capability of extracting non-trivial patterns from them. In this frame- work, we...

Estimation of emotions is an essential aspect in developing intelligent systems intended for crowded environments. However, emotion estimation in crowds remains a challenging problem due to the complexity in which human emotions are manifested and the capability of a system to perceive them in such conditions. This paper proposes a hierarchical...

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Wearable cameras allow users to record their daily activities from a user-centered (First Person Vision) perspective. Due to their favourable location, they frequently capture the hands of the user, and may thus represent a promising user-machine interaction tool for different applications. Existent First Person Vision, methods understand the...

In this work, we present a method for building grounded representations by structuring the sensorimotor data of an agent. The aim is to encode sensory inputs into internal states that describe action-environment couplings, or relations that connect elements in a scene to action concepts. Thus, the environment is represented regarding the...

Classifying frames, or parts of them, is a common way of carrying out detection tasks in computer vision. However, frame by frame classification suffers from sudden significant variations in image texture, colour and luminosity, resulting in noise in the extracted features and consequently in the decisions taken. Support Vector Machines have...

First Person Vision (Egocentric) video analysis stands nowadays as one of the emerging fields in computer vision. The availability of wearable devices recording exactly what the user is looking at is ineluctable and the opportunities and challenges carried by this kind of devices are broad. Particularly, for the first time a device is so...

Wearable cameras allow people to record their daily activities from a user-centered (First Person Vision) perspective. Due to their favorable location, wearable cameras frequently capture the hands of the user, and may thus represent a promising user-machine interaction tool for different applications. Existent First Person Vision methods...

With the growing availability of wearable technology, video recording devices have become so intimately tied to individuals, that they are able to record the movements of users' hands, making hand-based applications one the most explored area in First Person Vision (FPV). In particular, hand pose recognition plays a fundamental role in tasks...

Wearable cameras stand out as one of the most promising devices for the upcoming years, and as a consequence, the demand of computer algorithms to automatically understand the videos recorded with them is increasing quickly. An automatic understanding of these videos is not an easy task, and its mobile nature implies important challenges to be...

To understand the behavior of moving entities in a given environment, one should be capable of predicting their motion, that is, to model their dynamics. In a setting where different behaviors can arise, one can assume that each of them corresponds to different motivational states of observed entities. Here, those motivations are understood as...

Hand detection and segmentation methods stand as two of the most most prominent objectives in First Person Vision. Their popularity is mainly explained by the importance of a reliable detection and location of the hands to develop human-machine interfaces for emergent wearable cameras. Current developments have been focused on hand segmentation...

We introduced the concept of a community-based social recipe system which suggests recipes to groups of users based on available ingredients from these users (i.e. who can be from the same household or different households). In this paper we discuss the relevance and desirability of such a system and how it should be designed based on user...

This paper presents a method for observational learning in autonomous agents. A formalism based on deep learning implementations of variational methods and Bayesian filtering theory is presented. It is explained how the proposed method is capable of modeling the environment to mimic behaviors in an observed interaction by building internal...