Moving object detection by using GPS assisted image registration method

In this study, a Global Positioning System (GPS) assistance based system has been developed for unmanned ground vehicles (UGV) to detect moving objects along their route using a computer vision system. Before the real time application of the UGV, image models were created that represents a default background in specified horizontal positions of the specified coordinates on the route. This model is a type of feature matrix which is much smaller than the pure image matrices. The model matrices were recorded in the system database and a database relation was created between the model and its coordinate. The feature matrices of the images captured when the moment UGV arrived to the determined coordinates are compared with the models belong to present coordinate. As a result of the evaluation image frames are aligned with 2D image registration methods. The silhouettes of the objects are obtained by subtracting aligned frames. Thus, using this developed approach, there is no need for costly solutions to compensate for the noise generated by the moving camera. It was observed from the experiments that the system was able to detect the objects with 90% accuracy and it was able to run with 8% CPU loading and 0.057 s processing time per frame.