步态是生物特征识别领域的一个新兴热点，它有以下3大优势：远距离识别、非侵犯性和难于隐藏。由于当前提出的大量步态特征提取算法要么过于复杂，要么识别率不高，难以满足自动步态识别的需要，因此，为了进行准确快速的步态识别，提出了一种新的基于区域特征的快速步态识别方法。该方法首先将检测出的2维人体侧影分为头部、躯干和腿部3个区域；然后分别提取每个区域的目标面积；最后将这些面积特征和人体的宽高比特征一起构成步态特征矢量用于训练和识别。此外，还改进了一种新的N—best分类器，该分类器在一定程度上提高了算法的识别率。实验结果表明，该新方法不仅简单快速，而且在UCSD和CMU数据集上分别得到了90％和98％左右的高识别率。

Recognizing people by their gait is a recent research hotspot. Compared with other biometrics,gait has the following three advantages: distance recognition,uninvasive and difficult to conceal.A lot of research on the gait feature extraction has been done,but some of them are much expensive computation,while others are poor identification effect.A new fast gait recognition method based on the region object area is proposed in this paper.Firstly,we divide the two dimensional silhouette of the walker into three regions(head region,trunk region and legs region).Then their region object areas are computed respectively.Together with the ratio of the (silhouette's) height to width,the gait feature vectors are constructed to identify different subjects.Moreover,a kind of N-best classifier is improved in this paper.Experimental results show that the new method is not only simple and fast,but also very effective.It can also be used on different database.Recognition rate of approximately 90% on the UCSD database and over 98% on the CMU database are achieved.