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156 results on '"Brdiczka, Oliver"'

1. Characterizing User Behavior and Information Propagation on a Social Multimedia Network

Author

O'Donovan, Francis T., Fournelle, Connie, Gaffigan, Steve, Brdiczka, Oliver, Shen, Jianqiang, Liu, Juan, and Moore, Kendra E.

Subjects
Computer Science - Social and Information Networks, Physics - Physics and Society
Abstract

An increasing portion of modern socializing takes place via online social networks. Members of these communities often play distinct roles that can be deduced from observations of users' online activities. One such activity is the sharing of multimedia, the popularity of which can vary dramatically. Here we discuss our initial analysis of anonymized, scraped data from consenting Facebook users, together with associated demographic and psychological profiles. We present five clusters of users with common observed online behaviors, where these users also show correlated profile characteristics. Finally, we identify some common properties of the most popular multimedia content., Comment: 6 pages, 5 figures, 2 tables, to be published in the proceedings of the Int. Workshop on Social Multimedia Research (SMMR) 2013. 2013 IEEE

Published
2013
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3. Understanding Email Writers: Personality Prediction from Email Messages

Author

Shen, Jianqiang, Brdiczka, Oliver, Liu, Juan, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carberry, Sandra, editor, Weibelzahl, Stephan, editor, Micarelli, Alessandro, editor, and Semeraro, Giovanni, editor

Published
2013
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4. Inferring Personality of Online Gamers by Fusing Multiple-View Predictions

Author

Shen, Jianqiang, Brdiczka, Oliver, Ducheneaut, Nicolas, Yee, Nicholas, Begole, Bo, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Masthoff, Judith, editor, Mobasher, Bamshad, editor, Desmarais, Michel C., editor, and Nkambou, Roger, editor

Published
2012
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5. Situation Modeling Layer

Author

Kleindienst, Jan, Cuřín, Jan, Brdiczka, Oliver, Dimakis, Nikolaos, Karat, John, editor, Vanderdonckt, Jean, editor, Waibel, Alexander, editor, and Stiefelhagen, Rainer, editor

Published
2009
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6. Situation Modeling

Author

Brdiczka, Oliver, Crowley, James L., Cuřín, Jan, Kleindienst, Jan, Karat, John, editor, Vanderdonckt, Jean, editor, Waibel, Alexander, editor, and Stiefelhagen, Rainer, editor

Published
2009
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7. A Human-Centered Model for Detecting Technology Engagement

Author

Glasnapp, James, Brdiczka, Oliver, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, and Jacko, Julie A., editor

Published
2009
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12. Extracting Activities from Multimodal Observation

Author

Brdiczka, Oliver, Maisonnasse, Jérôme, Reignier, Patrick, Crowley, James L., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Gabrys, Bogdan, editor, Howlett, Robert J., editor, and Jain, Lakhmi C., editor

Published
2006
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14. Collaborative Paper-Based Annotation of Lecture Slides

Author

Steimle, Jurgen, Brdiczka, Oliver, and Muhlhauser, Max

Abstract

In a study of notetaking in university courses, we found that the large majority of students prefer paper to computer-based media like Tablet PCs for taking notes and making annotations. Based on this finding, we developed CoScribe, a concept and system which supports students in making collaborative handwritten annotations on printed lecture slides. It includes mechanisms for the paper-based sharing and semantic tagging of annotations and slides. Moreover, we present a novel visualization of shared handwritten annotations providing an integrated access to annotations from all learners. The results of a user study indicate that CoScribe efficiently supports student annotation and can be easily integrated into current annotation practice. (Contains 10 figures.)

Published
2009

19. Learning situation models in a smart home

Author

Brdiczka, Oliver, Crowley, James L., and Reignier, Patrick

Subjects
Human-computer interaction -- Analysis, Learning -- Models, Learning -- Evaluation
Abstract

This paper addresses the problem of learning situation models for providing context-aware services. Context for modeling human behavior in a smart environment is represented by a situation model describing environment, users, and their activities. A framework for acquiring and evolving different layers of a situation model in a smart environment is proposed. Different learning methods are presented as part of this framework: role detection per entity, unsupervised extraction of situations from multimodal data, supervised learning of situation representations, and evolution of a predefined situation model with feedback. The situation model serves as frame and support for the different methods, permitting to stay in an intuitive declarative framework. The proposed methods have been integrated into a whole system for smart home environment. The implementation is detailed, and two evaluations are conducted in the smart home environment. The obtained results validate the proposed approach. Index Terms--Context awareness, human-centered computing, machine learning, situation modeling, situation split.

Published
2009

27. Scene Text Access: A Comparison of Mobile OCR Modalities for Blind Users.

Author

Neat, Leo, Fu, Wai-Tat1, Pan, Shimei, Brdiczka, Oliver, Chau, Polo, Calvary, Gaelle, Neat, Leo, Peng, Ren, Qin, Siyang, Manduchi, Roberto, Neat, Leo, Fu, Wai-Tat1, Pan, Shimei, Brdiczka, Oliver, Chau, Polo, Calvary, Gaelle, Neat, Leo, Peng, Ren, Qin, Siyang, and Manduchi, Roberto

Abstract

We present a study with seven blind participants using three different mobile OCR apps to find text posted in various indoor environments. The first app considered was Microsoft SeeingAI in its Short Text mode, which reads any text in sight with a minimalistic interface. The second app was Spot+OCR, a custom application that separates the task of text detection from OCR proper. Upon detection of text in the image, Spot+OCR generates a short vibration; as soon as the user stabilizes the phone, a high-resolution snapshot is taken and OCR-processed. The third app, Guided OCR, was designed to guide the user in taking several pictures in a 360° span at the maximum resolution available by the camera, with minimum overlap between pictures. Quantitative results (in terms of true positive ratios and traversal speed) were recorded. Along with the qualitative observation and outcomes from an exit survey, these results allow us to identify and assess the different strategies used by our participants, as well as the challenges of operating these systems without sight.

Published
2019

28. SmartObjects

Author

Müller, Florian, primary, Schnelle-Walka, Dirk, additional, Grosse-Puppendahl, Tobias, additional, Günther, Sebastian, additional, Funk, Markus, additional, Luyten, Kris, additional, Brdiczka, Oliver, additional, Dezfuli, Niloofar, additional, and Mühlhäuser, Max, additional

Published
2018
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30. SmartObjects

Author

Schnelle-Walka, Dirk, primary, Müller, Florian, additional, Grosse-Puppendahl, Tobias, additional, Luyten, Kris, additional, Mühlhäuser, Max, additional, and Brdiczka, Oliver, additional

Published
2017
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32. Proceedings of the 1st joint workshop on Smart Connected and Wearable Things 2016

Author

Müller, Florian, Grosse-Puppendahl, Tobias, Mecella, Massimo, Luyten, Kris, Brdiczka, Oliver, Lanir, Joel, Schnelle-Walka, Dirk, Limonad, Lior, Kuflik, Tsvi, Mühlhäuser, Max, Müller, Florian, Grosse-Puppendahl, Tobias, Mecella, Massimo, Luyten, Kris, Brdiczka, Oliver, Lanir, Joel, Schnelle-Walka, Dirk, Limonad, Lior, Kuflik, Tsvi, and Mühlhäuser, Max

Abstract

These are the Proceedings of the 1st joint workshop on Smart Connected and Wearable Things (SCWT'2016, Co-located with IUI 2016). The SCWT workshop integrates the SmartObjects and IoWT workshops. It focusses on the advanced interactions with smart objects in the context of the Internet-of-Things (IoT), and on the increasing popularity of wearables as advanced means to facilitate such interactions.

Published
2016

36. SmartObjects

Author

Schnelle-Walka, Dirk, primary, Mühlhäuser, Max, additional, Radomski, Stefan, additional, Brdiczka, Oliver, additional, Huber, Jochen, additional, Luyten, Kris, additional, and Grosse-Puppendahl, Tobias, additional

Published
2015
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37. Proceedings of the 3rd IUI Workshop on Interacting with Smart Objects

Author

Schnelle-Walka, Dirk, Radomski, Stefan, Huber, Jochen, Brdiczka, Oliver, Luyten, Kris, Mühlhäuser, Max, Schnelle-Walka, Dirk, Radomski, Stefan, Huber, Jochen, Brdiczka, Oliver, Luyten, Kris, and Mühlhäuser, Max

Abstract

These are the Proceedings of the 3rd IUI Workshop on Interacting with Smart Objects. Objects that we use in our everyday life are expanding their restricted interaction capabilities and provide functionalities that go far beyond their original functionality. They feature computing capabilities and are thus able to capture information, process and store it and interact with their environments, turning them into smart objects.

Published
2014

38. Apprentissage des modèles de situations afin de fournir des services sensibles au contexte

Author

Brdiczka, Oliver, Laboratoire d'Informatique de Grenoble (LIG), Université Joseph Fourier - Grenoble 1 (UJF)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Institut National Polytechnique de Grenoble - INPG, and Prof. James L. Crowley(james.crowley@inrialpes.fr)

Subjects
découpage de situations, supervised situation learning scheme, role detection, situation split, apprentissage supervisé desituations, modélisation de contexte, acquisitionautomatique et évolution d'un modèle de situations, deterministic and probabilisticimplementation of situation models, découverte non-supervisé de situations, implémentationdéterministe et probabiliste d'un modèle de situations, context modeling, modèle de situations, situation model, automatic acquisition and evolution ofsituation models, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], unsupervised situation discovery, détection de rôles
Abstract

This thesis addresses the problem of learning situation models forproviding context-aware services in an intelligent environment. First, thenotion of context for modeling human behavior in an intelligent environmentis motivated and introduced. Context is represented by a situation modeldescribing environment, users and their activities. Two exampleimplementations for the situation model are proposed. A framework foracquiring and evolving different layers of a situation model is thenintroduced. Several novel learning methods are part of this framework: roledetection per entity, unsupervised extraction of situations from multimodaldata, supervised learning of situation representations, and the evolution ofa predefined situation model with feedback. The situation model serves asframe and support for the different methods, permitting to stay in anintuitive declarative framework. The proposed framework has been implementedand evaluated for an intelligent home environment.; Cette thèse porte sur l'apprentissage des modèles de situations afinde fournir des services sensibles au contexte dans un environnementintelligent. D'abord, nous motivons et introduisons la notion de contextepour la modélisation du comportement humain. Ce dernier est représenté par unmodèle de situations décrivant l'environnement, ses occupants et leursactivités. Nous proposons deux exemples d'implémentation du modèle desituations. Puis, nous introduisons un cadre conceptuel pour l'acquisitionautomatique et l'évolution des différentes couches d'un modèle de situations.Ce cadre regroupe différentes méthodes d'apprentissage: la détection de rôlespar entité, l'extraction non-supervisée de situations à partir de donnéesmultimodales, l'apprentissage supervisé de situations et l'évolution d'unmodèle de situations basée sur les retours de l'utilisateur. Ce cadreconceptuel ainsi que les méthodes associées ont été implémentées et évaluéesdans un environnement domestique augmenté.

Published
2007

39. Learning Situation Models for Providing Context-Aware Services

Author

Brdiczka, Oliver, Laboratoire d'Informatique de Grenoble (LIG), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF), Institut National Polytechnique de Grenoble - INPG, and Prof. James L. Crowley(james.crowley@inrialpes.fr)

Subjects
découpage de situations, supervised situation learning scheme, role detection, situation split, apprentissage supervisé desituations, modélisation de contexte, acquisitionautomatique et évolution d'un modèle de situations, deterministic and probabilisticimplementation of situation models, découverte non-supervisé de situations, implémentationdéterministe et probabiliste d'un modèle de situations, context modeling, modèle de situations, situation model, automatic acquisition and evolution ofsituation models, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], unsupervised situation discovery, détection de rôles
Abstract

This thesis addresses the problem of learning situation models forproviding context-aware services in an intelligent environment. First, thenotion of context for modeling human behavior in an intelligent environmentis motivated and introduced. Context is represented by a situation modeldescribing environment, users and their activities. Two exampleimplementations for the situation model are proposed. A framework foracquiring and evolving different layers of a situation model is thenintroduced. Several novel learning methods are part of this framework: roledetection per entity, unsupervised extraction of situations from multimodaldata, supervised learning of situation representations, and the evolution ofa predefined situation model with feedback. The situation model serves asframe and support for the different methods, permitting to stay in anintuitive declarative framework. The proposed framework has been implementedand evaluated for an intelligent home environment.; Cette thèse porte sur l'apprentissage des modèles de situations afinde fournir des services sensibles au contexte dans un environnementintelligent. D'abord, nous motivons et introduisons la notion de contextepour la modélisation du comportement humain. Ce dernier est représenté par unmodèle de situations décrivant l'environnement, ses occupants et leursactivités. Nous proposons deux exemples d'implémentation du modèle desituations. Puis, nous introduisons un cadre conceptuel pour l'acquisitionautomatique et l'évolution des différentes couches d'un modèle de situations.Ce cadre regroupe différentes méthodes d'apprentissage: la détection de rôlespar entité, l'extraction non-supervisée de situations à partir de donnéesmultimodales, l'apprentissage supervisé de situations et l'évolution d'unmodèle de situations basée sur les retours de l'utilisateur. Ce cadreconceptuel ainsi que les méthodes associées ont été implémentées et évaluéesdans un environnement domestique augmenté.

Published
2007

40. Détection automatique des groupes d'interactions

Author

Maisonnasse Jérôme and Brdiczka Oliver

Subjects
Activity recognition, Voice activity detection, Ubiquitous computing, Computer science, Perception, media_common.quotation_subject, Speech recognition, Intelligent environment, Turn-taking, Interpersonal communication, Hidden Markov model, media_common
Abstract

This work brings a new perception to intelligent environments for human activity recognition. To understand human activities, we need to differentiate users concerned and their interpersonal links. We propose a new group interaction detection tool based on an assumption that conversational turn taking is synchronized inside groups. We assess HMM-based and algorithmic approaches to build a detector which is able to segment interaction groups from speech detection. Both approaches show good results thus confirm the conversational hypothesis.

Published
2005

44. SmartObjects

Author

Schnelle-Walka, Dirk, primary, Huber, Jochen, additional, Radomski, Stefan, additional, Brdiczka, Oliver, additional, Luyten, Kris, additional, and Mühlhäuser, Max, additional

Published
2014
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46. Special Issue on Multimedia Technologies for E-learning

Author

Ludwig, Nadine, Knipping, Lars, Brdiczka, Oliver, Ludwig, Nadine, Knipping, Lars, and Brdiczka, Oliver

Subjects
Educational technology, Interactive multimedia, Internet in education
Abstract

Title from PDF title page (viewed on Sept. 10, 2009).

Published
2009

47. Proceedings of the 2nd IUI Workshop on Interacting with Smart Objects

Author

Schnelle-Walka, Dirk, Huber, Jochen, Lissermann, Roman, Brdiczka, Oliver, Luyten, Kris, Mühlhäuser, Max, Schnelle-Walka, Dirk, Huber, Jochen, Lissermann, Roman, Brdiczka, Oliver, Luyten, Kris, and Mühlhäuser, Max

Abstract

These are the Proceedings of the 2nd IUI Workshop on Interacting with Smart Objects. Objects that we use in our everyday life are expanding their restricted interaction capabilities and provide functionalities that go far beyond their original functionality. They feature computing capabilities and are thus able to capture information, process and store it and interact with their environments, turning them into smart objects.

Published
2013

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