Stereo matching method for non-coding circular reference points based on motion consistency

Reference point-based fusion of multi-view measurement data is a popular method of object digitization that relies on the accurate matching of reference points in the images. However, due to the lack of coding information in the linear-structured light measurement, establishing a correspondence with the reference points becomes a challenging task. As the pose of a handheld linear-structured light measurement device undergoes very minor changes across neighboring views, this paper exploits this property and proposes a novel method of stereoscopic matching of non-coded reference circle points for a binocular linear-structured light measurement system. First, the polar line constraint is used to determine the initial set of matches, and these matches are used to compute the distance and direction of motion of the camera across neighboring views. The motion information is then used to eliminate the instances of mismatches from the initial results. Experiments on a self-locating linear-structured light measurement system show that the proposed algorithm can achieve an accurate and stable stereoscopic matching of binocular non-coded reference circle points.