Parallax-Robust Hexahedral Panoramic Video Stitching

Abstract

In this paper, we present a parallax-robust hexahedral panoramic video stitching method. An efficient three-stage stitching procedure is proposed. In the preprocessing stage, layered feature points matching strategy extracts feature matches lying in different depth layers. In the rough alignment stage, based on the first layer of feature matches, global projective warping estimates and refines camera parameters by considering the constraints among all cameras to avoid accumulated errors. With camera parameters, image pixels are roughly mapped onto a spherical surface. In the refined alignment stage, based on multiple layers of feature matches, layered content-preserving warping further aligns abundant feature pairs exploited from multiple depth layers, so as to alleviate ghosting caused by large parallax. Experimental results show that our method can effectively stitch panoramic video without noticeable parallax errors.