基于Gabor滤波和特征三角形的驾驶员面部跟踪  

Driver’s Face Tracking Based on Feature Triangle and Gabor Filter

作　　者：杨秋芬[1] 胡豁生[1] 桂卫华[1] 

机构地区：[1]中南大学信息工程学院,长沙410083

出　　处：《计算机工程与应用》2006年第23期16-18,共3页Computer Engineering and Applications

基　　金：国家自然科学基金资助项目(编号:50374079);国家973重点基础研究规则资助项目(编号:2002cb12203)

摘　　要：文章提出了一种驾驶员面部跟踪的鲁棒、有效的视频图像人脸跟踪算法。该算法根据水平投影曲线获取眼睛、鼻孔和嘴等区域构造特征三角形(包括等腰三角形和直角三角形),再根据刚体约束生成潜在人脸跟踪矩形区域。再采用二维Gabor核函数构造最优滤波器48个,在特征跟踪矩形区域内获取48个人脸特征点。该算法能够在不同尺寸、不同光照、不同姿态和不同表情甚至不同噪音情况下跟踪人脸有效率达97.81%。A robust and efficient driver＇s face tracking algorithm in video that can detect faces is presented in this paper.The algorithm ensures the localization of mouth,nose and eyes with horizontal gray-level projection region to construct feature triangle including isosceles triangle and right triangle for face tracking.The algorithm creates latency rectangle region with rigid body constraints.Then it constitutes forty-eight optimization filters according to 2D-Gabor kernel functions to acquire forty-eight feature points inside the latency rectangle region.Our algorithm can conquer different sizes,different lighting conditions,varing pose and expression,and noise problems.The algorithm can also detect faces from the side way.Experimental results demonstrate that an approximately 98% success rate is achieved.

关 键 词：GABOR滤波 特征三角形 核函数 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]