基于局部线性映射神经网络和亮度补偿的彩色人脸检测

人脸识别是一个具有广阔应用前景和极富挑战性的研究课题。作为自动人脸识别系统的第一步，快速有效的人脸检测至关重要。利用颜色信息进行人脸检测，具有直观、简单、快速的特点，非常适用于作为自动人脸识别系统的人脸粗定位环节。该文提出一种基于局部线性映射（ Ｌ Ｌ Ｍ）神经网络和亮度自适应补偿的人脸区域检测算法，根据待检测图像上每点的颜色值判断它属于人体区域还是背景区域，从而框出可能的人脸区域。实验表明，此算法对于实验室背景下的人脸检测取得了较好的效果。一方面可以较好地区分人脸区域和背景区域，甚至与人脸颜色比较相近的背景区域，同时对实验室环境下各种光照条件的变化具有很好的鲁棒性。

LLM neural networks and compensation for light condition based color face detection

A utomatic face recognition is one of the most challenging task in fields of computer vision and pattern recognition with broad application prospective, and face detection is the first critical step in full automatic face recognition system. Based on local linear map (LLM) neural networks and adaptive compensation for light condition a face detection algorithm is proposed. The algorithm can locate the face area in color camera images of complex laboratory scenes according to the color value of every pixel. Experimental results show that the algorithm can rapidly distinguish the face areas from most background areas and has a good robustness to the change of light condition.