Research Projects (2007)
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- 3D Computer Vision 3D reconstruction Aerial Vision Augmented Reality Augmented Video Best Paper Award Biometrics Caleydo Computer Graphics Computer Vision Convex Optimization Coordinate transformations detection face Fingerprint Georeferencing GPU GUI HOG Human Computer Interaction Image Labelling Industrial Applications Information Visualization integral imaging Interaction Interaction Design Machine Learning Medical computer vision Medical Visualization Mixed Reality Mobile computing Mobile phone Model Multi-Display Environments Multiple Perspectives Object detection Object recognition Object reconstruction Object Tracking On-Line Learning Robotics Segmentation Shape analysis shape from focus SLAM Software Projects Structure from Motion Surveillance SVM Symmetry Tracking Fusion Tracking, Action Recognition User Interfaces Variational Methods Virtual reality and augmented reality Visual Tracking Visualization
ICAO Face Normalization and Analysis
The goal of this project is the research and development of state of the art computer vision and object recognition algorithms to analyze face portrait images according to the ICAO (International Civil Aviation Organization) standards and specifications. Therefore a close cooperation with Siemens IT Solutions and Services Biometric Center in Graz exists, where the Biometry group is developing a software solution for this purpose.
Current passports issued in the European Union contain biometric data like e.g. digital photographs and fingerprints in order to uniquely identify its owner. To be able to read passports all over the world, the ICAO has specified a number of guidelines and requirements for the structure of these biometric features. In case of face portrait images, examples for these requirements are neutral appearance, eyes opened, mouth closed, frontal pose, straight-looking eyes, properly-sitting eye-glasses, or uncovered faces. Since these analysis steps have to be performed in an automatic fashion, each of these requirements imposes certain computer vision research challenges which are tackled in this research project. Examples for the topics involved in these analysis steps are model-based segmentation using active shape and active appearance models, fast and robust AdaBoost based machine learning algorithms for face and face component detection, or classification of facial expressions using multi-classifier fusion approaches.