Robust moving object detection from a moving video camera using neural network and kalman filter

Abstract

Detecting motion of objects in images, while the camera is moving, is a complicated task. In this paper, we propose a novel method to effectively solve this problem by using Neural Network and Kalman Filter. This technique uses parameters of camera motion to overcome problems caused by error in the image processing outputs. We have implemented this technique in the MRL Middle Size Soccer Robots. The experimental results show a low error rate of 2.2% which suggests that the combined approach performs significantly better than the traditional techniques. © 2009 Springer Berlin Heidelberg.