Automatic detection and tracking of human faces in video sequences are considered fundamental in many applications, such as face recognition, video surveillance and human-computer interface. In this study, we propose a technique for real-time robust facial tracking in human facial videos based on a new algorithm for face detection in color images. As a part of face tracking, the Kalman filter algorithm is used to predict the next face detection window and smooth the tracking trajectory. Experiments on the five benchmark databases demonstrate the ability of the proposed algorithm in detecting and tracking faces in difficult conditions.

Rough-Fuzzy system-based real-time face tracking

PETROSINO, Alfredo;SALVI, Giuseppe
2013

Abstract

Automatic detection and tracking of human faces in video sequences are considered fundamental in many applications, such as face recognition, video surveillance and human-computer interface. In this study, we propose a technique for real-time robust facial tracking in human facial videos based on a new algorithm for face detection in color images. As a part of face tracking, the Kalman filter algorithm is used to predict the next face detection window and smooth the tracking trajectory. Experiments on the five benchmark databases demonstrate the ability of the proposed algorithm in detecting and tracking faces in difficult conditions.
1-60132-253-4
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/31088
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