嵌入式系统中实时行人检测方法

随着计算机技术的不断发展，智能自动化的人数检测系统不断产生.人数检测对于企业或机构的信息化管理至关重要.传统人数检测方法因为肢体遮挡以及光照变化导致准确率较低.提出了针对人头特征的垂直检测方法，该特征可以保证在人流密度大的情况下无法被遮挡.该方法首先提取前景图像的梯度方向直方图特征，并通过SVM检测人头目标，利用头部的颜色特征，在相邻帧中使用MeanShift算法跟踪人头目标.根据人头目标轨迹进行过线检测，算法在嵌入式系统上进行了应用与测试，实验表明算法有较好的实时性与准确率.

Real-Time Pedestrian Detection Method in Embedded System

With the development of computer technology, the intelligent and automatic pedestrian detecting system continues to emerge. The pedestrian detecting system is an important part of the information management for enterprises and institutions. The traditional method has a lower accuracy due to limb occlusion and light changes. This study proposes a vertical detection method for the head features, which can ensure that the features cannot be blocked even in high flow density. Firstly, the gradient histogram feature of the foreground image is extracted and the head target is detected by SVM. The MeanShift algorithm is used to track the head target in the adjacent frame by using the color feature of the head. The pedestrian is detected according to the target track. The algorithm is applied and tested in the embedded system. The experiment results show that the method is effective and accurate.