Inhalt

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   Acknowledgments
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   Abstract
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   Contents
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  Introduction
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  Scope and Contribution
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   Facial Communicative Signals
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   Valence Recognition
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   Task-Oriented Human-Robot Interaction
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   Challenges
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   Thesis Structure
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  Facial Communicative Signals
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  Human Face Perception
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   Physiological Basis
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   Behavioral Studies
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   Face Processing Features
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   Developmental Aspects
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   Conclusion
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   Facial Communicative Signals
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   Head Gestures
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   Eye Gaze
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   Facial Expressions
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   Conclusion
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  Valence Recognition
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   Selection of a Suitable Human-Robot Interaction Scenario
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   Object-Teaching Scenario and User Study
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   Video Database Description
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   Comments from the Participants
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   Interactive Behavior
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   Deployed Software
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   Valence Recognition Task and Ground Truth Data
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  Display of Facial Communicative Signals
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   Head Gestures
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   Eye Gaze
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   Facial Expressions
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   FCS Display in the Related Study of Barkhuysen et al. Barkhuysen2005
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   Conclusion
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  Human Valence Recognition Performance
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   Procedure
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   Results
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   Conclusion
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   Related Works
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   The Study of Barkhuysen et al. Barkhuysen2005
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   The Interaction Context
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  Automatic Recognition of Facial Communicative Signals
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  Face Detection
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   Knowledge-Based Methods
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   Feature Invariant Approaches
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   Template Matching Methods
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   Appearance-Based Methods
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   Boosting-Based Face Detection Approach of Viola and Jones Viola2004
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   Encara Face Detection Approach of Castrillón et al. Castrillon2007
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   Head Gesture Recognition
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   Appearance Template Methods
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   Detector Arrays
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   Nonlinear Regression Methods
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   Manifold Embedding Methods
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   Flexible Models
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   Geometric Methods
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   Tracking Methods
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   Eye Gaze Recognition
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   Facial Expression Recognition
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   Static Approaches
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   Dynamic Approaches
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   Descriptive Recognition and Interpretation
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   Current Research Trends
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  Face Representation and Facial Feature Extraction
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   Active Appearance Models
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   Constrained Local Models
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   Gabor Energy Filters
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  A Static Baseline Approach
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   Face Detection
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   Postprocessing
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  Facial Feature Extraction
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   Active Appearance Models
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   Gabor Energy Filters
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   Raw Face Images
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   Deployed Software
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   Evaluation
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   Majority Voting Over Frames
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   Classification with Mean Feature Vectors
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   Comparison to the Human Recognition Performance
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   Conclusion
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   A Dynamic Recognition Approach
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  Classification based on Reference Subsequences
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   Discriminative Subsequence Detection
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   Reference Subsequence Selection
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   Nearest-Neighbor-based Classification
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   Biased Classification
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   Parameter Optimization
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   Implementation
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   Related Approaches
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   Shapelets
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   Logical Shaplets
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   Classification with Discriminative Subsequences by Nowozin et al. Nowozin2007
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   Facial Expression Recognition Approach of Buenaposada et al. Buenaposada2008
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   Conclusion
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  Evaluation
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   Person-Specific Classification with Individual AAMs
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   Person-Specific Classification with Generic AAMs
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   Generalization to New Persons
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   Constrained Local Models for Feature Extraction
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   Conclusion
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   Conclusion
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  Possible Application Scenarios
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   A Social Robot at Home
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   Supporting the Training of Artificial Agents using Reinforcement Learning
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  Outlook
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   Improving the Dynamic Recognition Approach
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   Interesting Questions for Future Research
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  Appendix
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   Instructions for the Subjects of the Object-Teaching Study
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   Utterances of Biron in the Object-Teaching Study
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   Questionnaire for the Subjects of the Object-Teaching Study
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   Instructions for the Subjects of the Valence Recogniton Study
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   Questionnaire for the Subjects of the Valence Recogniton Study
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   Implementation of the Dynamic Recognition Approach
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   Feature Vector Dimensionality
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   Previous Publications
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   References
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   Bibliography