Fiducial marker based on projective invariant for augmented reality

Fiducial marker based Augmented Reality has many applications. So far the inner pattern of the fiducial marker is always used to encode the markers. Thus a large portion of the fiducial marker image is used for encoding instead of providing corresponding feature points for pose accuracy. This paper presents a novel method which utilizes directly the projective invariant contained in the positional relation of the corresponding feature points to encode the marker. The proposed method does not require the region of pattern image for encoding any more and can provide more corresponding feature points so that higher pose accuracy can be achieved easily. Many related approaches such as cumulative distribution function, reprojection verification and robust process are proposed to overcome the problem of sensibility of the projective invariant. Experimental results show that the proposed fiducial marker system is reliable and robust, and can provide higher pose accuracy than that achieved by existing fiducial marker systems.