Face Image Analysis
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Recent progress in the field of Computer Vision allows intuitive
interaction via gesture or facial expressions between humans and technical
systems. This project aims at determining facial expressions from camera
images in real-time. Model-based image interpretation techniques have
proven to be a successful method for extracting such high-level
information from single images and image sequences. Models rely on a
priori knowledge to reduce the large amount of image data to a small
number of model parameters. This representation of the image content
facilitates and accelerates the subsequent interpretation task. In order
to extract high-level information, model parameters have to be estimated
that best describe the face within a given image. However, correctly
estimated model parameters forms the basis of various more applications
such as gaze detection or gender estimation.
Our demonstrator for facial expression estimation has been presented at
several events with political audience and on TV.
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Research Topics
- Face Detection, Face Model Fitting, Head Tracking
- Facial Expression Recognition, Emotion Recognition
- Objective Functions, Learning Objective Functions
- Color Detection, Adaptive Skin Color Classification
Application Domain
- Multi-Joint Action
