Self-Location Estimation of a Moving Camera Using the Map of Feature Points and Edges of Environment

Applications as visual navigation of mobile robot with image sensor and mixed/augmented reality have been investigated actively. Many of these techniques require the localization of human or robot. In this report, we propose a novel method for estimating the position of a camera by using edge and feature point information in time-series of images. The technique can be applied to the indoor environment and the environment spatial model including feature points is obtained by tracking background feature points with the position of camera. The prediction model image is generated based on trajectory of the moving camera from the spatial model and the camera position is estimated by correction of model image from comparison with the input image.