A non-rigid motion estimation algorithm for yawn detection in human drivers

This work focuses on the estimation of possible fatigue or drowsiness by detecting the occurrence of yawns with human drivers. An image processing technique has been proposed to analyse the deformation occurring on driver's face and accurately identify the yawn from other types of mouth opening such as talking and singing. The algorithm quantifies the degree of deformation on lips when a driver yawns. The image processing methodology is based on study of non-rigid motion patterns on 2D images. The analysis is done on a temporal sequence of images acquired by a camera. A shape-based correspondence of templates on contours of a particular region is established on the basis of curvature information. The shape similarity between the contours is analysed, after decomposing with wavelets at different levels. Finally, the yawn is correlated with fatigue-induced behaviour of drivers on a simulator.

[1]  Alex Pentland,et al.  Facial expression recognition using a dynamic model and motion energy , 1995, Proceedings of IEEE International Conference on Computer Vision.

[2]  R A Peters,et al.  Automatic segmentation of ultrasound images using morphological operators. , 1991, IEEE transactions on medical imaging.

[3]  Haiyan Wang,et al.  Geometric active deformable models in shape modeling , 2000, IEEE Trans. Image Process..

[4]  Surendra Ranganath,et al.  Contour extraction from cardiac MRI studies using snakes , 1995, IEEE Trans. Medical Imaging.

[5]  S. Morimoto Signal control setting for speeding vehicle control and its effects , 1999, Proceedings 199 IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (Cat. No.99TH8383).

[6]  Yongmin Kim,et al.  A multiple active contour model for cardiac boundary detection on echocardiographic sequences , 1996, IEEE Trans. Medical Imaging.

[7]  I. Miki A study of traffic signals with a localizing function for visually-impaired persons , 1999, Proceedings 199 IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (Cat. No.99TH8383).

[8]  David F. Dinges,et al.  Perclos: A valid psychophysiological measure of alertness as assessed by psychomotor vigilance , 1998 .

[9]  George N. Votsis,et al.  Emotion recognition in human-computer interaction , 2001, IEEE Signal Process. Mag..

[10]  H. Li Computer recognition of human emotions , 2001, Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing. ISIMP 2001 (IEEE Cat. No.01EX489).

[11]  Walter W. Wierwille Overview of research on driver drowsiness definition and driver drowsiness detection , 1995 .

[12]  Shigeo Morishima,et al.  Emotion space for analysis and synthesis of facial expression , 1993, Proceedings of 1993 2nd IEEE International Workshop on Robot and Human Communication.

[13]  James S. Duncan,et al.  Shape-based tracking of left ventricular wall motion , 1997, IEEE Transactions on Medical Imaging.

[14]  P. Ekman Unmasking The Face , 1975 .

[15]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[16]  Nicolaos B. Karayiannis,et al.  Detection of microcalcifications in digital mammograms using wavelets , 1998, IEEE Transactions on Medical Imaging.

[17]  Pertti Roivainen,et al.  3-D Motion Estimation in Model-Based Facial Image Coding , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  John S. Duncan,et al.  Measurement of end diastolic shape deformity using bending energy , 1988, Proceedings. Computers in Cardiology 1988.

[19]  I. Daubechies Orthonormal bases of compactly supported wavelets , 1988 .

[20]  P. K. Dutta,et al.  Non-rigid cardiac motion quantification from 2D image sequences based on wavelet synthesis , 2001, Image Vis. Comput..

[21]  Toshio Fukuda,et al.  Traffic signal networks simulator with learning emotional algorithm , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[22]  Alan Wee-Chung Liew,et al.  Region-based approach to robust lip contour extraction , 2000 .

[23]  P. K. Dutta,et al.  A GA based approach for boundary detection of left ventricle with echocardiographic image sequences , 2003, Image Vis. Comput..

[24]  R J Fairbanks,et al.  RESEARCH ON VEHICLE-BASED DRIVER STATUS/PERFORMANCE MONITORING; DEVELOPMENT, VALIDATION, AND REFINEMENT OF ALGORITHMS FOR DETECTION OF DRIVER DROWSINESS. FINAL REPORT , 1994 .

[25]  Jennifer Healey,et al.  Toward Machine Emotional Intelligence: Analysis of Affective Physiological State , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  H. Shimizu,et al.  A systematic signal control of congestion lengths , 1999, Proceedings 199 IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (Cat. No.99TH8383).

[27]  Xinhua Zhuang,et al.  Image Analysis Using Mathematical Morphology , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.