Model-based 3-D object tracking using projective invariance

Abstract

This paper describes a method of three-dimensional object tracking by projective invariance. Usually, projective invariance has been used for object recognition and its property discards the need for cumbersome camera calibration to obtain metric information. We focus on the fact the projective invariance is not only regarded as recognition cues but also able to verify the status of a 3-D object for visual tracking. With projective invariance relevant to points, we develop a fast and reliable visual tracking strategy by combining a recognition module using projective invariance, window-based corner trackers for object's corner tracking and a visibility checking module. The proposed method is experimented in single IBM-PC platform successfully.