Real-time and accurate extrinsic camera parameter estimation using feature landmark database for augmented reality

Abstract

In the field of augmented reality (AR), many kinds of vision-based extrinsic camera parameter estimation methods have been proposed to achieve geometric registration between real and virtual worlds. Previously, a feature landmark-based camera parameter estimation method was proposed. This is an effective method for implementing outdoor AR applications because a feature landmark database can be automatically constructed using the structure-from-motion (SfM) technique. However, the previous method cannot work in real time because it entails a high computational cost or matching landmarks in a database with image features in an input image. In addition, the accuracy of estimated camera parameters is insufficient for applications that need to overlay CG objects at a position close to the user's viewpoint. This is because it is difficult to compensate for visual pattern change of close landmarks when only the sparse depth information obtained by the SfM is available. In this paper, we achieve fast and accurate feature landmark-based camera parameter estimation by adopting the following approaches. First, the number of matching candidates is reduced to achieve fast camera parameter estimation by tentative camera parameter estimation and by assigning priorities to landmarks. Second, image templates of landmarks are adequately compensated for by considering the local 3-D structure of a landmark using the dense depth information obtained by a laser range sensor. To demonstrate the effectiveness of the proposed method, we developed some AR applications using the proposed method.