PDF(4961 KB)
PDF(4961 KB)
PDF(4961 KB)
驾驶人眼睛局部区域定位算法
Driver's eye region location algorithm
基于机器视觉的驾驶人疲劳检测系统,通过对驾驶人眼睛动作的分析实现对驾驶人疲劳状态的估计。眼睛区域的准确定位是保证疲劳检测精度的前提条件。然而,实际行车过程中,驾驶人头部姿态随机、快速变化会造成眼睛区域定位精度的严重下降。该文在基于主动形状模型(ASM)算法实现驾驶人眼睛区域粗定位的基础上,针对ASM模型在实际检测过程中的姿态适应性较低与定位精度不高的问题,提出局部ASM模型来增强ASM算法的姿态适应性; 进一步引入平均合成精确滤波器(ASEF)算法与ASM算法相结合的思路提高对眼睛区域的定位精度; 同时,提出单、双眼相结合的ASEF算法来提高眼睛虹膜中心定位的鲁棒性。实验结果表明: 该算法对于驾驶人头部姿态变化具有较强的适应性,能够实现眼睛区域的准确定位。
Driver drowsiness estimates can be realized by analyses of the drivers' eye movements based on a machine vision system. However, the system requires accurate eye region recognition in the driver's facial image. Random, rapid changes of the head posture complicate locating the eye region in real driving scenarios. The active shape model (ASM) can be used to coarsely locate the eye region. This study uses a local ASM model to enhance the head posture adaptability of the ASM algorithm. Then, the average of synthetic exact filters (ASEF) algorithm and the ASM are combined to improve the eye region location precision. A single eye ASEF and a double eyes ASEF are integrated to more robustly identify the iris center location. Tests show that the algorithm has strong head posture adaptability and can robustly and accurately identify the eye region location.
| [1] | Ji Q, Yang X J. Real-ime eye, gaze, and face pose tracking for monitoring driver vigilance[J]. Real-ime Imaging, 2002, 8: 357-377. |
| [2] | Hu S Y, Zheng G T. Driver drowsiness detection with eyelid related parameters by support vector machine[J]. Expert Systems with Applications, 2009, 36: 7651-7658. |
| [3] | 张伟. 基于机器视觉的驾驶人疲劳状态识别关键问题研究[D]. 北京: 清华大学, 2011. ZHANG Wei. Research on Key Issues in Computer Vision Based Driver Drowsiness Recognition[D]. Beijing: Tsinghua University, 2011. (in Chinese) |
| [4] | 中国交通年鉴社. 中国交通年鉴2011[M]. 北京: 中国交通年鉴社, 2011. Year Book House of China Transportation & Communication. Year Book of China Transportation & Communication 2011[M]. Beijing: Year Book House of China Transportation & Communication, 2011. (in Chinese) |
| [5] | 张伟, 成波, 张波. 驾驶人眼睛定位与跟踪算法的研究[J]. 汽车工程, 2012, 34(10): 889-893. ZHANG Wei, CHENG Bo, ZHANG Bo. A research on the algorithm for driver's eye position and tracking[J]. Automotive Engineering, 2012, 34(10): 889-893. (in Chinese) |
| [6] | Grace R, Byrne V E, Bierman D M, et al.A drowsy driver detection system for heavy vehicle [C]// Digital Avionics Systems Conference (17th DASC). Bellevue: The Institude of Electrical and Electronics Engineers Inc, 1998: 136-1-136-8 |
| [7] | Yullie A L, Hallian P W, Cohen D S. Feature extraction from faces using deformable templates[J]. International Journal of Computer Vision, 1992, 8(2): 99-111. |
| [8] | Fasel I, Fortenberry B, Movellan J. A generative framework for real time object detection and classification[J]. Computer Vision and Image Understanding, 2005, 98(1): 182-210. |
| [9] | Pentland A, Moghaddam B, Starner T. View-ased and modular eigenspaces for face recognition [C]// IEEE Society Conference on Computer Vision and Pattern Recognition. Seattle, WA: IEEE Computer Society Press, 1994: 84-91. |
| [10] | Cootes T F, Twining C J, Taylor C J. Diffeomorphic statistical shape models[J]. Image and Vision Computing, 2008, 26(3): 326-332. |
| [11] | 张伟, 成波, 张波. 驾驶人眼睛区域的鲁棒性定位算法研究[J]. 物理学报, 2012, 61(6): 060701-1-060701-9. ZHANG Wei, CHENG Bo, ZHANG Bo. Research on eye location algorithm robust to driver's pose and illumination [J]. Acta Phys Sin, 2012, 61(6): 060701-1-060701-9. (in Chinese) |
| [12] | Bolme D S, Draper B A, Beveridge J R. Average of synthetic exact filters [C]// IEEE Conference on Computer Vision and Pattern Recognition. Miami, FL: IEEE, 2009: 2105-2112. |
| [13] | Vitomir S, Jerneja Z G, Nikola P. Principal directions of synthetic exact filters for robust real-ime eye localization[J]. Biometrics and ID Management, 2011, 6583: 180-192. |
| [14] | Freund Y, Schapire R E. A decision-heoretic generalization of on-ine learning and an application to boosting[J]. Journal of Computed and System Science, 1997, 55(1): 119-139. |
| [15] | GAO Wen, CAO Bo, SHAN Shiguang, et al.The CAS-EAL large-cale Chinese face database and baseline evaluations[J]. IEEE Trans on System Man and Cybernetics: Part A, 2008, 38(1): 149-161. |
| [16] | Milborrow S, Morkel J, Nicolls F. The MUCT Landmarked Face Database [DB/OL]. Pattern Recognition Association of South Africa, 2010. http://www.milbo.org/muct. |
| [17] | Jesorsky O, Kirchberg K J, Frischholz R W. Robust face detection using the Hausdorff distance [C]// Conference on Audio-and Video-ased Biometric Person Authentication. Berlin: Springer, 2001: 90-95. |
/
| 〈 |
|
〉 |
