Jacob Foytik

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Fine-grain head pose estimation from imagery is an essential operation for many human-centered systems, including pose independent face recognition and human-computer interaction (HCI) systems. It is only recently that estimation systems have evolved past coarse level classification of pose and concentrated on fine-grain estimation. In particular, the state(More)
Design of an efficient modular architecture for detection of multiple faces in video stream is presented in this paper. Face detection is the first step in many surveillance and security applications such as face recognition, face authentication for banking and security access control, monitoring and tracking, etc. The algorithm used for this hardware(More)
We propose a real time system for person detection, recognition and tracking using frontal and profile faces. The system integrates face detection, face recognition and tracking techniques. The face detection algorithm uses both frontal face and profile face detectors by extracting the ’Haar’ features and uses them in a cascade of boosted classifiers. The(More)
Real-time tracking and recognizing multiple faces in complex environments has the ability to provide efficient security automation to large areas. Previous research has shown that Kalman filter techniques paired with the traditional face detection methods can be used to track one or more faces in a viewing region, but prove unreliable under variant(More)
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