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Fritsch, Jan Nikolaus: Vision-based recognition of gestures with context. 2003
Inhalt
Introduction
Categorization of Gestures
Recognition of Manipulative Gestures
Contribution
Outline
Symbolic Action Detection
Related Work
The Situated Artificial Communicator Domain
The Assembly Model for baufix® Parts
Object Recognition
Assembly Recognition
Detecting Actions by Symbolic Inference
Two-Hand Model to Capture Actual Hand Contents
Detecting Scene Changes with the Part Memory
Inferring Actions from Scene Changes
Limitations of the Symbolic Approach
Summary
Recognizing Human Gestures
Modeling Human Activities
Recognizing Activities
Kalman Filters
Hidden Markov Models
Particle Filtering
Summary
Finding Human Hands in Color Images
Properties of Skin-color
Related Work
Extracting Features with Image Processing
Adaptive Skin Color Segmentation
Modeling the Skin Color Distribution
Measuring the Skin Locus
Detecting Faces in Images
Initializing the Skin Color Model
Performing Skin Color Segmentation of Input Images
Updating the Skin Color Model
Faster Segmentation based on Regions of Interest
Compromises necessary for Real-Time Image Processing
Results
Summary
Visual Activity Recognition
Related Work
Tracking Skin-Colored Objects
Recognition of Construction Activities
Results
Summary
Integrating Sensory and Symbolic Information for Action Recognition
Related Work
Extending Particle Filtering with Context Information
Extracting Context Information for Hand Gestures
Revisiting the Different Types of Gestures
Relations between Hand Motions and Objects
Defining Object Context for Manipulative Gestures
Integrated Action Recognition using Object Context
Evaluating the Recognition of Assembly Construction Actions
Recognizing Manipulative Gestures in an Office Environment
Task-based Object Recognition
Summary
Action Recognition in the Situated Artificial Communicator
Improving the Human-Machine Interface
Fusing with Visual Assembly Recognition
Providing Hypotheses for Object Recognition
Summary
Summary and Conclusion
Bibliography
Index