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中文摘要：
人流量统计信息在交通控制、公共场所、商业分析等领域具有重要意义。针对传统方法的不足，提出了一种基于特征匹配的人流量统计方法。该方法的第一阶段是采集少量有代表性的样本，每个样本由特征向量和对应的人数组成，并根据人数进行分类。第二阶段进行人流量统计，即提取一个运动视频段的特征向量，然后把该特征向量与样本库的每类样本进行马氏距离特征匹配，得到最佳的人数估计。实验表明，该算法具有较高的检测率，而且能够满足实时性的要求。
英文摘要：
The information of the pedestrian flows has great significance in many areas, such as traffic control, public places, business analysis. According to the shortages of conventional methods, a statistics of pedestrian flows method based on feature matching is presented in this paper. This method consists of two stages. The first stage is collecting some representative samples which consist of feature vector and the corresponding pedestrian number, and then classify all samples according to pedestrian number. The second stage is to count the pedestrian： the feature vector of a motion video is extracted, which is then compared with each class of samples based on Mahalanobis distance feature matching to estimate the optimal number of pedestrians. The experimental results show that the method has high detection probability and satisfies the requirement of real-time application.
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