A neural approach to extract foreground from human movement images

In recent years many approaches to foreground extraction from images related to human movement have been presented. The foreground extraction represents a pre-processing procedure to be implemented in a system for capturing human movement in order to facilitate the tracking of anatomical landmarks on human bodies. In this work, an approach based on an unsupervised neural network has been studied: a Kohonen map has been designed to recognize and separate structures characterizing foreground and background. The proposed technique is fully automatic and its performance has been compared with those of two further approaches based on differences between foreground and background images. In order to quantify the segmentation quality, an already validated, objective, and automatic criterion has been used. The obtained results are adequate with the final aim of the application and show the feasibility of the proposed approach.