Lecture Notes in Computer Science 9277

Transcription

1 Lecture Notes in Computer Science 9277 Commenced Publication in 1973 Founding and Former Series Editors: Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen Editorial Board David Hutchison Lancaster University, Lancaster, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M. Kleinberg Cornell University, Ithaca, NY, USA Friedemann Mattern ETH Zurich, Zürich, Switzerland John C. Mitchell Stanford University, Stanford, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen TU Dortmund University, Dortmund, Germany Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Gerhard Weikum Max Planck Institute for Informatics, Saarbrücken, Germany

2 More information about this series at

3 Albert Ali Salah Ben J.A. Kröse Diane J. Cook (Eds.) Human Behavior Understanding 6th International Workshop, HBU 2015 Osaka, Japan, September 8, 2015 Proceedings 123

4 Editors Albert Ali Salah Computer Engineering Dept Bogazici University Bebek, Istanbul Turkey Ben J.A. Kröse HvA University of Applied Sciences Amsterdam, Noord-Holland The Netherlands Diane J. Cook Washington State University Pullman, WA USA ISSN ISSN (electronic) Lecture Notes in Computer Science ISBN ISBN (ebook) DOI / Library of Congress Control Number: LNCS Sublibrary: SL6 Image Processing, Computer Vision, Pattern Recognition, and Graphics Springer Cham Heidelberg New York Dordrecht London Springer International Publishing Switzerland 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (

5 Preface Domains where human behavior understanding is a crucial need (e.g., robotics, human-computer interaction, affective computing, and social signal processing) rely on advanced pattern recognition techniques to automatically interpret complex behavioral patterns generated when humans interact with machines or with other humans. This is a challenging problem where many issues are still open, including the joint modeling of behavioral cues taking place on different time scales, the inherent uncertainty of machine detectable evidences of human behavior, the mutual influence of people involved in interactions, the presence of long term dependencies in observations extracted from human behavior, and the important role of dynamics in human behavior understanding. The Sixth Workshop on Human Behavior Understanding (HBU), organized as a satellite to the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UBICOMP 2015, Osaka), gathered researchers dealing with the problem of modeling human behavior under its multiple facets (expression of emotions, display of relational attitudes, performance of individual or joint actions, imitation, etc.). The HBU workshops, previously organized jointly with the International Conference on Pattern Recognition (ICPR 2010, Istanbul), the International Joint Conference on Ambient Intelligence (AMI 2011, Amsterdam), the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012, Algarve), ACM Multimedia (ACM MM 2013, Barcelona), and the European Conference on Computer Vision (ECCV 2014, Zürich), have highlighted different aspects of this problem since their inception. The 6th HBU workshop focused on behavior analysis for the elderly. A better life for the aging population requires facilitating technologies, digital assistance, smart and multimodal monitoring, and technologies for health assessment and intervention. While different aspects of mobile platforms and ubiquitous computing are tackled in several venues, the HBU workshop specifically solicited human behavior analysis solutions that clearly advance the field, and chart the future of behavior-sensing for the elderly, which brings its own issues and challenges. The two keynote speakers of the workshop were Dr. Tanzeem Choudhury (Cornell University) and Jakob E. Bardram (IT University of Copenhagen). In the first keynote talk, entitled Tracking Behavioral Symptoms of Mental Illness and Delivering Personalized Interventions Using Smartphones and Wearables, Dr. Choudhury argued that continuous and unobtrusive sensing of behaviors has tremendous potential to support the lifelong management of mental illnesses by: (1) acting as an early warning system to detect changes in mental well-being, (2) delivering context-aware, personalized micro-interventions to patients when and where they need them, and (3) by significantly accelerating patient understanding of their illness. She discussed her group s work on turning sensor-enabled mobile devices into well-being monitors and instruments for administering real-time/real-place interventions.

6 VI Preface It is obvious that there is much to learn from behavior traits collected in a semi-automatic fashion from ordinary smartphones. These traces can be used for analysis, as well as prediction. In his keynote talk, entitled What is the Role of Personal Health Technology in Mental Health for the Elderly? Dr. Bardram shared his experiences in designing and evaluating personal health technology for mental disorders (like depression) with a focus on elderly users. Based on their results from smartphone-based behavior sampling and mood forecasting, he discussed how to design personal health technology for mental health, with a specific focus on the design space of the elderly population. This proceedings volume contains the papers presented at the workshop and an overview contribution of the focus theme by the co-chairs. We have received 15 submissions. Each paper was peer-reviewed by at least two members of the Technical Program Committee, with three reviews per paper on the average. Eleven papers were accepted, revised for the proceedings in accordance with reviewer comments, and presented at the workshop. The papers have been organized into thematic sections on Interacting with the Elderly, Learning Behavior Patterns, and Mobile Solutions. Together with the invited talks, the focus theme was covered broadly and extensively by the workshop. We would like to take the opportunity to thank our Program Committee members and reviewers for their rigorous feedback, our authors and our invited speakers for their contributions, and our media sponsor Noldus for the help in disseminating news about the workshop. September 2015 Albert Ali Salah Ben J.A. Kröse Diane J. Cook

7 Organization Conference Co-chairs Albert Ali Salah Ben J.A. Kröse Diane J. Cook Boğaziçi University, Turkey HvA University of Applied Sciences and University of Amsterdam, The Netherlands Washington State University, USA Technical Program Committee Gilles Adda Elisabeth André Juan Augusto Lynne Baillie Jakob Bardram Nadia Berthouze Özlem Durmaz İncel Gwenn Englebienne Cem Ersoy Parisa Eslambolchilar Jesus Favela Kaori Fujinami Stefan Göbel Dilek Hakkani-Tür Ahmed Helmy Tristan Henderson Jesse Hoey Larry Holder Hayley Hung Alexandro Jaimes Michel Klein Tsvika Kuflik Bruno Lepri Janne Lindqvist Paul Lukowicz Nuria Oliver Francis Quek Elisa Ricci Parisa Rashidi CNRS LIMSI, France Universität Augsburg, Germany Middlesex University, UK Glasgow Caledonian University, UK IT University of Copenhagen, Denmark University College London, UK Galatasaray University, Turkey University of Twente, The Netherlands Boğaziçi University, Turkey Swansea University, UK CICESE, Mexico Tokyo University of Agriculture and Technology, Japan Technische Universität Darmstadt, Germany Microsoft Research, USA University of Florida, USA University of St. Andrews, UK University of Waterloo, Canada Washington State University, USA Delft University of Technology, The Netherlands Yahoo New York City, USA Vrije Universiteit Amsterdam, The Netherlands University of Haifa, Israel Fondazione Bruno Kessler, Italy Rutgers University, USA DFKI, Germany Telefonica, Spain Texas A&M University, USA Fondazione Bruno Kessler, Italy University of Florida, USA

8 VIII Organization Stephan Sigg Enrique Vidal Katarzyna Wac University of Göttingen, Germany Universitat Politècnica de València, Spain University of Geneva, Switzerland Additional Reviewers F. Serhan Daniş Dean Kramer Can Tunca Remzi Yavuz

9 Contents Behavior Analysis for Elderly Albert Ali Salah, Ben J.A. Kröse, and Diane J. Cook Interactions with Elderly Understanding the User s Acceptance of a Sensor-Based Ambient Assisted Living Application Christina Jaschinski and Somaya Ben Allouch Sleep Analysis for Elderly Care Using a Low-Resolution Visual Sensor Network Mohamed Eldib, Francis Deboeverie, Wilfried Philips, and Hamid Aghajan How Are You Doing? Enabling Older Adults to Enrich Sensor Data with Subjective Input Marije Kanis, Saskia Robben, and Ben Kröse Rethinking the Fusion of Technology and Clinical Practices in Functional Behavior Analysis for the Elderly Juhi Ranjan and Kamin Whitehouse Mobile Solutions Push or Delay? Decomposing Smartphone Notification Response Behaviour Liam D. Turner, Stuart M. Allen, and Roger M. Whitaker Estimating the Perception of Physical Fatigue Among Older Adults Using Mobile Phones Netzahualcóyotl Hernández and Jesús Favela Online Prediction of People s Next Point-of-Interest: Concept Drift Support Mehdi Boukhechba, Abdenour Bouzouane, Bruno Bouchard, Charles Gouin-Vallerand, and Sylvain Giroux

10 X Contents Learning Behavior Patterns Abnormal Behavioral Patterns Detection from Activity Records of Institutionalized Older Adults Valeria Soto-Mendoza, Jessica Beltrán, Edgar Chávez, Jehú Hernández, and J. Antonio García-Macías Contextualized Behavior Patterns for Ambient Assisted Living Paula Lago, Claudia Jiménez-Guarín, and Claudia Roncancio Activity Patterns in Stroke Patients - Is There a Trend in Behaviour During Rehabilitation? Adrian Derungs, Julia Seiter, Corina Schuster-Amft, and Oliver Amft Identification of Basic Behavioral Activities by Heterogeneous Sensors of In-Home Monitoring System Vasily Moshnyaga, Tanaka Osamu, Toshin Ryu, and Koji Hashimoto Author Index