Towards a Video Annotation System using Face Recognition
A face recognition software framework was developed to lay the foundation for a future video annotation system. The framework provides a unified and extensible interface to multiple existing implementations of face detection and recognition algorithms from OpenCV and Wawo SDK. The framework supports face detection with cascade classification using Haar-like features, and face recognition with Eigenfaces, Fisherfaces, local binary pattern histograms, the Wawo algorithm and an ensemble method combining the output of the four algorithms. An extension to the cascade face detector was developed that covers yaw rotations. CAMSHIFT object tracking was combined with an arbitrary face recognition algorithm to enhance face recognition in video. The algorithms in the framework and the extensions were evaluated on several different test databases with different properties in terms of illumination, pose, obstacles, background clutter and imaging conditions. The results of the evaluation show that the algorithmic extensions provide improved performance over the basic algorithms under certain conditions.
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