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.