This paper presents an algorithm for real time and robust human face tracking against pictures and other objects. It is based on Haar-like features, skin segmentation and motion information for face detection. Face tracking is performed using particle filter which depends on skin color and probabilistic face model. Basically, the employed features for face detection are Haar-like. We employ PCA...

Face and hand tracking are important areas of research, related to adaptive human-computer interfaces, and affective computing. In this article we have introduced two new methods for boundary detection of the human face in video sequences: (1) edge density thresholding, and (2) fuzzy edge density. We have analyzed these algorithms based on two main factors: convergence speed and stability again...

Successful face detection and facial feature extraction is crucial for for a variety of applications, including speech recognition and fatigue monitoring. Detecting and tracking faces in a moving automobile is challenging because of a variety of reasons. Among these reasons are changing poses, extreme lighting changes and shadowing. In this paper, we investigate two approaches for shadow compen...

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This paper addresses the issue of face detection and tracking in the context of a mobile videoconferencing application. While the integration of such technology into a mobile videophone is advantageous, allowing face stabilisation, reduced bandwidth requirements and smaller display sizes, its deployment in such an environment may not be straightforward, since most face detection methods reporte...

We present the first purely event-based approach for face detection using an ATIS, a neuromorphic camera. We look for pairs of blinking eyes by comparing local activity across the input frame to a predefined range, which is defined by the number of events per second in a specific location. If within range, the signal is checked for additional constraints such as duration, synchronicity and dist...

This paper describes Pittsburgh Pattern Recognition’s participation in the face detection and tracking tasks for the CLEAR 2007 evaluation. Since CLEAR 2006, we have made substantial progress in optimizing our algorithms for speed, achieving better than real-time processing performance for a speed-up of more than 500× over the past two years. At the same time, we have maintained the high level ...

Driver fatigue detection plays an important role in intelligent transportation systems for driving safety. Therefore, it becomes an essential research issue these years. Recently, Horng and Chen proposed a real-time driver fatigue detection system based on eye tracking and dynamic template matching. In their work, the driver fatigue detection system consists of four parts: face detection, eye d...

In this paper, in order to implement a computer vision-based recognition system of driving fatigue. In addition to detecting human face in different light sources and the background conditions, and tracking eyes state combined with fuzzy logic to determine whether the driver of the physiological phenomenon of fatigue from face of detection. Driving fatigue recognition has been valued highly in ...