A visual approach for driver inattention detection

Hybrid computer vision system for drivers' eye recognition and fatigue monitoring

Yawning detection has a variety of important applications in a driver fatigue detection, well-being assessment of humans, driving behavior monitoring, operator attentiveness detection, and understanding the intentions of a person with a tongue disability. In all of the above applications, an automatic detection of yawning is one important system component. In this paper, we design and implement such automatic system, using computer vision, which runs on a computationally limited embedded smart camera platform to detect yawning. We use a significantly modified implementation of the Viola-Jones algorithm for face and mouth detections and, then, use a backprojection theory for measuring both the rate and the amount of the changes in the mouth, in order to detect yawning. As proof-of-concept, we have also implemented and tested our system on top of an actual smart camera embedded platform, called APEX from CogniVue Corporation. In our design and implementations, we took into consideration the practical aspects that many existing works ignore, such as real-time requirements of the system, as well as the limited processing power, memory, and computing capabilities of the embedded platform. Comparisons with existing methods show significant improvements in the correct yawning detection rate obtained by our proposed method.

Yawning Detection Using Embedded Smart Cameras

http://repositorio.uchile.cl/bitstream/handle/2250/126131/Perez_Claudio_Face_and_iris.pdf?sequence=1

Face and iris localization using templates designed by particle swarm optimization

ing and non-profit use of the material is permitted with credit to the source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. Publisher assumes no responsibility liability for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained inside. After this work has been published by the Advanced Robotic Systems International, authors have the right to republish it, in whole or part, in any publication of which they are an author or editor, and the make other personal use of the work. © 2007 Advanced Robotic Systems International www.ars-journal.com Additional copies can be obtained from: publication@ars-journal.com First published June 2007 Printed in Croatia A catalogue record for this book is available from the Austrian Library. Humanoid Robots, New Developments, Edited by Armando Carlos de Pina Filho p. cm. ISBN 978-3-902613-00-4 1. Humanoid Robots. 2. Applications. I. Armando Carlos de Pina Filho

Humanoid Robots: New Developments

This paper presents a real-time face detection algorithm for locating faces in images and videos. This algorithm finds not only the face regions, but also the precise locations of the facial components such as eyes and lips. The algorithm starts from the extraction of skin pixels based upon rules derived from a simple quadratic polynomial model. Interestingly, with a minor modification, this polynomial model is also applicable to the extraction of lips. The benefits of applying these two similar polynomial models are twofold. First, much computation time are saved. Second, both extraction processes can be performed simultaneously in one scan of the image or video frame. The eye components are then extracted after the extraction of skin pixels and lips. Afterwards, the algorithm removes the falsely extracted components by verifying with rules derived from the spatial and geometrical relationships of facial components. Finally, the precise face regions are determined accordingly. According to the experimental results, the proposed algorithm exhibits satisfactory performance in terms of both accuracy and speed for detecting faces with wide variations in size, scale, orientation, color, and expressions.

A novel method for detecting lips, eyes and faces in real time

This paper proposes a novel method to detect faces in color images with a wide range of variations in head poses, face tilting, facial expressions and body interferences. The proposed algorithm can locates not only the face regions, but also some important facial components such as month corners and eyes. The experimental results show that the proposed method exhibits satisfied performance in both well-controlled and real-world environments. The performance is also compared with that of a face detector developed by CMU to demonstrate the major strength of the proposed algorithm.

Chi-Jaung Huang

Papers

A novel method for detecting lips, eyes and faces in real time

Feature-based detection of faces in color images