Dorothy Monekosso. Paolo Remagnino Yoshinori Kuno. Editors. Intelligent Environments. Methods, Algorithms and Applications.

Transcription

1 Dorothy Monekosso. Paolo Remagnino Yoshinori Kuno Editors Intelligent Environments Methods, Algorithms and Applications ~ Springer

2 Contents Preface List of Contributors VB XV 1 Intelligent Environments: Methods, Algorithms and Applications... Dorothy N. Monekosso, Paolo Remagnino, and Yoshinori Kuno 1.1 Intelligent Environments I What Is An Intelligent Environment? How Is An Intelligent Environment Built? Technology for Intelligent Environments Research Projects Private Spaces Public Spaces Middleware Chapter Themes in This Collection Conclusion References A Pervasive Sensor System for Evidence-Based Nursing Care Support Toshio Hori, Yoshifumi Nishida, and Shin'ichi Murakami 2.1 Introduction Evidence-Based Nursing Care Support Background of the Project Concept of Evidence-Based Nursing Care Support Initial Goal of the Project: Falls Prevention Second Goal of the Projecl: Obtaining ADL of Inhabitants Related Work ix

3 x Contents 2.4 Overview and Implementations of the System Overview of the Evidence-Based Nursing Care Support System System Implementations Experiments and Analyses Tracking a Wheelchair for Falls Prevention Activity Transition Diagram: Transition of Activities in One Day Quantitative Evaluation of Daily Activities Probability of "Toi]et" Activity Discussion of the Experimental Results Prospect of the Evidence-Based Nursing Care Support System Conclusions 31 Referenccs Anomalous Behavior Detection: Supporting Independent Living Dorothy N. Monekosso and Paolo Remagnino 3.1 Introduction Related work Methodology Unsupervised Classification Techniques Using HMM to Model Behavior Experimental Setup and Data Collection Noisy Data: Sources of Error Learning activities Experimental Results Instance Class Annotation Data Preprocessing Models: Unsuperviscd Classification: C1ustering and Allocation of Activities to Clusters Behaviors: Discovering Patterns in Activities Behaviors: Discovering Anomalous Patterns of Activity Discussion Conclusions References Sequential Pattern Mining for Cooking-Support Robot, 51 Yasushi Nakauchi 4.1 Introduction ] 4.2 System Design Inference from Series of Human Actions, Time Sequence Data Mining Human Behavior Inference Algorithm Activity Support of Human 57

4 Contents XI 4.3 Implementation IC Tag System Inference of Human's Next Action Cooking Support Interface Experimental Results Conc1usions References Robotic, Sensory and Problem-Solving Ingredients for the Future Horne Amedeo Cesta, Luca locchi, G. Riccardo Leone, Daniele Nardi, Federico Pecora, and Riccardo Rasconi 5.1 Introduction Components of the Multiagent System The Robotic Platform Mobility Subsystem The Interaction Manager Environmental Sensors for People Tracking and Posture Recognition Monitoring Activities of Daily Living Schedule Representation and Execution Monitoring Constraint Management in the ROBOCARE Context From Constraint Violations to VerbalInteraction Multiagent Coordination Infrastructure Casting the MAC Problem to DCOP Cooperatively Solving the MAC Problem Conc1usions References Ubiquitous Stereo Vision for Human Sensing Ikushi Yoda and Katsuhiko Sakae 6.1 Introduction Ubiquitous Stereo Vision Concept of Ubiquitous Stereo Vision " Server-Client Model for USV Real Utilization Cases Hierarchical Utilization of 3D Data and Personal Recognition Acquisition of 3D Range Information Projection to Floor Plane Recognition of Multiple Persons and Interface Pose Recognition for Multiple People Personalldentification Interface for Space Control Human Monitoring in Open Space (Safety Management Application) Monitoring Railroad Crossing Station Platform Edge Safety Management 103

5 XII Contents Monitoring Huge Spaee Conclusion and Future Work 105 Referenecs Augmenting Professional Training, an Ambient Intelligence Approach, 109 B. Zhan, D.N. Monekosso, S. Rush, P. Remagnino, and S.A. Velastin 7.1 Introduetion Color Tracking of People Counting People by Spatial Relationship Analysis Simple People Counting Algorithm Graphs of Blobs Estimation of Distanee Between Blobs Temporal Pyramid für Distance Estimation Probabilistic Estimation of Groupings Grouping Blobs Experimental Results Conclusions 124 References Stereo Omnidirectional System (SOS) and Its Applications 127 Yutaka Satoh and Katsuhiko Sakaue 8.1 Introduction System Configuration Image integration Generation of Stable Images at Arbitrary Rotation An example Applieation: Intelligent Electric Wheelchair Overview System Configuration Obstacle Detection Gesture / Posture Detection Conclusions 140 References Video Analysis for Ambient Intelligence in Urban Environments..., 143 Andrea Prati and Rita Cueehiara 9.1 Introduction Visual Data for Urban AmI Video Surveillance in Urban Environment The LAICA Project Automatie Video Proeessing for People Traeking People Detection and Traeking from Single Static Camera People Detection and Tracking from Distributed Cameras 152

6 Contents Xlll People Detection and Tracking from Moving Cameras 154 9A Privacy and Ethical Issues 155 References From Monomodal to Multimodal: Affect Recognition Using Visual Modalities " 161 Hatice Gunes and Massimo Piccardi 10.1 Introduction Organization of the Chapter From Monomodal to Multimodal: Changes and Challenges Background Research Data Collection Data Annotation 169 1O.3A Synchrony/Asynchrony Between Modalities Data Integration/Fusion Information Complementarity/Redundancy Information Content of Modalities 176 IOA Monomodal Systems Recognizing Affective Face or Body Movement Multimodal Systems Recognizing Affect from Face and Body Movement Project 1: Multimodal Affect Analysis for Future Cars " Project 2: Emotion Analysis in Man-Machine Interaction Systems Project 3: Multimodal Affect Recognition in Learning Environments A Project 4: FABO-Fusing Face and Body Gestures for Bimodal Emotion Recognition Multimodal Affect Systems: The Future 185 References Importance of Vision in Human-Robot Communication: Understanding Speech Using Robot Vision and Demonstrating Proper Actions to Human Vision " 191 Yoshinori Kuno, Michie Kawashima, Keiichi Yamazaki, and Akiko Yamazaki 11.1 Introduction Understanding Simplified Utterances Using Robot Vision Inexplicit Utterances Information Obtained by Vision Language Processing A Vision Processing Synchronization Between Speech and Vision Experiments 199

7 xiv Contents 11.3 Communicative Head Gestures for Museum Guide Robots Observations from Guide-Visitor Interaction Prototype Museum Guide Robot Experiments at a Museum 206 IIA Conclusion 208 References 209 Index 211