Augmented reality based on online trifocal tensors estimation using multiple features

Abstract

Purpose – The purpose of this paper is to present a novel registration method for augmented reality (AR) systems based on robust estimation of trifocal tensor using point and line correspondence simultaneously.Design/methodology/approach – The proposed method distinguishes itself in following three ways: first, to establish the world coordinate system, the restriction that the four specified points must form an approximate square is relaxed, the only requirement is that these four points should not be collinear. Second, besides feature points, line segments are also used to calculate the needed trifocal tensors. The registration process can still be achieved even without the use of feature points. Third, to estimate trifocal tensors precisely, progressive sample consensus (PROSAC) is used instead of random sample consensus to remove outliers.Findings – As shown in the experiments, the proposed method really enhances the usability of this system. To calculate trifocal tensor, a PROSAC based algebraic minim...