复杂背景下基于运动特征的人面定位

Human Face Location Based on Motion Information in a Complex Background

对传统的光流算法进行了改进 ,提出了一种新的分割图像的方法 ,并与传统的神经网络算法相结合 ,通过两步定位模型 ,进行人面定位。其中 ,搜索定位是本系统最关键的一步 ,采用两步法 ,首先进行候选人面区域的分割 ,然后进行基于神经网络的人面精确定位。实验结果表明 ,采用的两步法在复杂背景下具有运动特征的人面定位过程中 ,具有实时性、鲁棒性好及实用性强的诸多优点 ,通过实验 ,取得了满意的效果。并且所涉及的人面定位系统将是后阶段完整人面识别系统的重要组成部分。

This paper proposes an improvement for the traditional Optical Algorithm, and presents a new way to image segmentation in a complex background. In addition, combined with the neural network, the system can locate the possible human faces successfully by means of two-step location model. In our system, the searching and locating of the human face is the most important stage. According to this, the authors adopt the two-step way to run, firstly they take up the segmentation of the candidate human face areas and then the accurate face locating based on the neural network is used. This algorithm is fast and robust. Experimental results with real scene images are given out there, and all these prove that two-step method gains many advantages in the course of human face location with motion information, such as real-time, robustness and practicality. In addition, the proposed system is also the fundamental and important part of the perfect human face recognition system.