Detection of Human Bodies from the Background in an Image Using Piecewise Linear-Support Vector Machine

- Detection of the human bodies from the background in an image is challenged by the view and posture variation
problem. In this paper, a piecewise linear support vector machine (PL-SVM) method is used for solving the problem of
identification of humans in an image, which is challenged by the view and posture variation problem. The motivation is, by
using the piecewise discriminative function for constructing a non-linear classification boundary that can differentiate
multi-view and multi-posture human bodies from the backgrounds in a high dimensional feature space. A PL-SVM
training is designed as an iterative procedure of feature space division and linear SVM training, aiming at the maximized
marginality of local linear SVM’s. Each piecewise SVM model is responsible for subspace, corresponding to a human
cluster of a special view or posture. In the PL-SVM, a cascaded detector is proposed with block orientation features and a
histogram of oriented gradient features. This identification of humans in an image is implemented by using mat lab. By
using this method, we can also detect the presence of humans in videos also