Gait Recognition Based On Support Vector Machines

Human gait is the way of people's walk that is only behavioral characteristics of biometrics which can be detected and measured at a distance. Compared with previous conventional physic-logical biometrics (e.g. fingerprints, iris and face), the gait has unexampled advantages such as difficult to hide and disguise, simple collection, identification from far away even in low-resolution and so on. But gait recognition rate is relatively low. However, gait is a relatively new and emergent behavioral biometric, and gait recognition has received growing interest within the computer vision community recently, is currently the active research topic in the domain of visual analysis of human motion.Gait recognition analysis of human usually includes gait motion segment, feature extract, and recognition. This interest is driven by a wide spectrum of promising applications in many areas such as virtual reality, smart surveillance, perceptual user interface. Gait analysis aims at attempting to detect, track and identify people, and more generally, to understand human behaviors, from image sequences involving humans. This paper provides a comprehensive survey of recent developments of vision-based human motion analysis, and it keeps up with the latest research.This paper proposed a new gait recognition approach based on PCA(Principal Component Analysis) and support vector machine(SVM).First, we detect the moving gait from each image sequence. In this paper we use the gait database which each sequence has only one person walk in the same background. Two background modeling methods are studied: RGB and gray, comparing the two methods, we chose the first which is more effective.Second, the foreground area is obtained by background subtraction, viz. the body silhouette. The outer contour of the silhouette is projected along the midline of the body to obtain the fore-and-aft Midline Projection Vectors, which are then combined into one dimensional vector as the gait feature.Then, eigenspace transformation based on PCA is applied to time-varying project...