Abstract

In this paper we present a component based person detection system that is capable of detecting frontal, rear and near side views of people, and partially occluded persons in cluttered scenes. The framework that is described here for people is easily applied to other objects as well. The motivation for developing a component based approach istwofold: rst, to enhance the performance of person detection systems on frontal and rear views of people and second, to develop a framework that directly addresses the problem of detecting people who are partially occluded or whose body parts blend in with the background. The data classi cation is handled by several support vector machine classi ers arranged in two layers. This architecture is known as Adaptive Combination of Classi ers (ACC). The system performs very well and is capable of detecting people even when all components of a person are not found. The performance of the system is signi cantly better than a full body

Citations