Driver’s head pose estimation using a hierarchical classification on an effective feature space

Abstract

This paper introduces a direct accountability technique for the real-time estimation of the head’s position and orientation. Unlike existing works which rely on feature extraction either in the image domain or in three-dimensional space, our proposed approach based on a hierarchical expert classification will estimate the head pose for real-time applications, specifically for driver assistance systems. We proposed a method for feature extraction which aims at keeping only the angle-related features, independent of identity. We then used a hierarchical algorithm for classification which divides the whole space into smaller spaces. Moreover, we made a performance study aiming at evaluating the accuracy of the proposed approach. Experimental results show that the proposed features are able to describe the pose of the driver face image successfully, with a performance in agreement with the actual poses. This approach is not only useful for automobile safety and security but also can help severely handicapped people and can be used in collision prevention systems and other driving applications.

Keywords

Head pose estimation human–machine interface intelligent automotive systems driver behaviors surveillance

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References

Trivedi

. A two-stage head pose estimation framework and evaluation. Pattern Recognit 2008; 41(3): 1138–1158.

Guo

. A new algorithm for analyzing driver’s attention state. In: IEEE intelligent vehicles symposium, 2009, Xi’an, People’s Republic of China, pp.21–23.

Mamatha

Ramachandran

. Automatic eyewinks interpretation system using face orientation recognition for human-machine interface. Int J Comput Sci Network Security 2009; 9(5): 155–163.

Murphy-Chutorian

Trivedi

. Hybrid head orientation and position estimation (HyHOPE): A system and evaluation for driver support. In: IEEE intelligent vehicles symposium, 2008, Eindhoven, the Netherlands, pp.512–517.

Baskar

De Schutter

Hellendoorn

. Model-based predictive traffic control for intelligent vehicles: dynamic speed limits and dynamic lane allocation. In: IEEE intelligent vehicles symposium, 2008, Eindhoven, the Netherlands, pp.174–179.

Murphy-Chutorian

Trivedi

. Head pose estimation and augmented reality tracking: an integrated system and evaluation for monitoring driver awareness. IEEE Trans Intell Transp Syst 2010; 11(2): 300–311.

Doshi

Trivedi

. On the roles of eye gaze and head dynamics in predicting driver’s intent to change lanes. IEEE Trans Intell Transp Syst 2009; 10(3): 453–462.

Gong

Sherrah

Liddell

. Support vector machine based multi-view face detection and recognition. Image Vision Comput 2004; 22(5): 413–427.

Liu

Luo

. A new representation method of head images for head pose estimation. In: IEEE international conference on image processing, 2009, Cairo, Egypt, pp.3585–3588.

10.

Voit

Nickel

Stiefelhagen

. Neural network-based head pose estimation and multiview fusion. In: Multimodal technologies for perception of humans, 2007, Berlin, Germany, pp.291–298.

11.

Wang

Sung

. EM enhancement of 3D head pose estimated by point at infinity. Image Vision Comput 2007; 25(12): 1864–1874.

12.

Xiao

Baker

Matthews

Kanade

. Real-time combined 2D+3D active appearance models. In: IEEE conference on computer vision and pattern recognition, 2004, Washington, USA, pp.535–542.

13.

Murphy-Chutoria

Trivedi

. Head pose estimation in computer vision: a survey. IEEE Trans Pattern Analysis Machine Intell 2009; 31(4): 607–626.

14.

Ghaffari

Rezvan

Khodayari

Vahidi-Shams

. A robust head pose tracking and estimating aprouch for driver assistant system. In: IEEE international conference on vehicular electronics and safety, 2011, Beijing, People’s Republic of China, pp.180–186.

15.

Joshi

Kamathe

. Quantification of retinex in enhancement of whether degraded image. In: International conference on audio, language and image processing, 2008, Shanghai, People’s Republic of China, pp.1229–1233.

16.

Land

. An alternative technique for the computation of the designator in the retinex theory of color vision. Proc Natl Acad Sci USA 1986; 83(10): 3078–3080.

17.

Jobson

Rahman

Woodell

. Properties and performance of a center/surround retinex. IEEE Trans Image Processing 1997; 6(3): 451–462.

18.

Bian

Zhang

. Retinex image enhancement techniques: algorithm, application and advantages. Final project report for EE264 image processing and reconstruction, 2002.

19.

Gourier

Hall

Crowley

. Estimating face orientation from robust detection of salient facial structures. In: International workshop on visual observation of deictic gestures, 2004, Cambridge, UK, pp.17–25.

20.

Turk

Pentland

. Eigenfaces for recognition. J Cognitive Neurosci 1991; 3(1): 71–86.

21.

Pentland

Moghaddam

Stamer

. View-based and modular eigenspaces for face recognition. In: IEEE computer society conference on computer vision and pattern recognition, 1994, Seattle, WA, USA, pp.84–91.

22.

Huang

. Locating nose-tips and estimating head poses in images by tensorposes. IEEE Trans Circuits Syst Video Technol 2009; 19(1): 90–102.

23.

Cormen

Leiserson

Rivest

Stein

. Introduction to algorithms, 2nd ed. Cambridge, MA: MIT Press, 2001.

24.

Huang

. Evaluation of head pose estimation for studio data. In: International workshop on classification of events activities and relationships, 2006, Southampton, UK, pp.281–290.

25.

Gourier

Maisonnasse

Hall

Crowley

. Head pose estimation on low resolution images. In: International workshop on classification of events activities and relationships, 2006, Southampton, UK, pp.281–290.

26.

Stiefelhagen

. Estimating head pose with neural networks – results on the Pointing’04 ICPR workshop evaluation data. In: Pointing 2004 workshop: visual observation of deictic gestures, 2004, Cambridge, UK.

27.

Beauchemin

Varcheie

Gagnon

. COBVIS-D: A computer vision system for describing the cephalo-ocular behavior of drivers in a driving simulator. In: International conference on Image analysis and recognition, 2009, Halifax, Canada, pp.604–615.

28.

Liu

. A vehicle anti-theft and alarm system based on computer vision. In: IEEE international conference on vehicular electronics and safety, 2005, Xi’an, People’s Republic of China, pp.326–330.

29.

Doshi

Trivedi

. Attention estimation by simultaneous observation of viewer and view. In: IEEE computer society conference on computer vision and pattern recognition workshops, 2010, San Francisco, CA, USA, pp.21–27.

30.

Tran

Trivedi

. Driver assistance for ’keeping hands on the wheel and eyes on the road. In: IEEE international conference on vehicular electronics and safety, 2009, Pune, India, pp.97–101.