Robust Real-Time Face Detection
International Journal of Computer Vision
Overview of the Face Recognition Grand Challenge
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Face Description with Local Binary Patterns: Application to Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
2D and 3D face recognition: A survey
Pattern Recognition Letters
Recognition of faces in unconstrained environments: a comparative study
EURASIP Journal on Advances in Signal Processing - Special issue on recent advances in biometric systems: a signal processing perspective
Assessment of time dependency in face recognition: an initial study
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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In this article, a virtual environment for realistic testing of face analysis systems under uncontrolled conditions is proposed. The key elements of this tool are a simulator, and real face and background images taken under real-world conditions with different acquisition conditions, such as indoor or outdoor illumination. Inside the virtual environment, an observing agent, the one with the ability to recognize and detect faces, can navigate and observe the face images, at different distances, and angles. During the face analysis process, the agent can actively change its viewpoint and relative distance to the faces in order to improve the recognition results. The virtual environment provides all behaviors to the agent (navigation, positioning, face's image composing under different angles, etc.), except the ones related with the analysis of faces (detection, recognition, pose estimation, etc.). In addition we describe different kinds of experiments that can be implemented for quantifying the face analysis capabilities of agents and provide usage example of the proposed tool in evaluating a face recognition system in a service robot.