Panorama stitching using overlap area weighted image plane projection and dynamic programming for visual localization

Abstract

This paper presents a panorama stitching system of using only one single camera to generate an omnidirectional scene map for visual localization tasks. Instead of assuming that the overlapping area keeps constant for two adjacent images, the overlapping area is estimated and further refined by using matched SURF feature pairs. By doing this, the dependency of the system on camera setup and its motion could be reduced, and hence it will be a more robust system. To consider an environment with highly symmetric or repeated features, the regional SURF feature detection is applied to lower down the fault error during the SURF feature matching. To reduce the distortion within the resulting panorama image, the overlapping area weighted image plane projection is used to successfully create a panorama image. Furthermore, to prevent ghost effect during stitching panorama image, the dynamic programming algorithm is used to find an optimal path to stitch two adjacent images. The proposed algorithm has been tested in two indoor environments and related qualitative and quantitative results are analyzed in detail.