Research on Panorama Generation from a Multi-Camera System by Object-Distance Estimation

Abstract

Panoramic imagery from multi-camera systems often suffers the problem of geometric mosaicking errors due to eccentric errors between the optical centers of cameras and variations in object-distances within the panoramic environment. In this paper, an inverse rigorous panoramic imaging model was derived completely for a panoramic multi-camera system. Additionally, we present an estimation scheme aimed at extracting object-distance information to enhance the seamlessness of panoramic image stitching. The essence of the scheme centers around our proposed object-space-based image matching algorithm called the Panoramic Vertical Line Locus (PVLL). As a result, panoramas were generated using the proposed inverse multi-cylinder projection method, utilizing the estimated object-distance information. The experiments conducted on our developed multi-camera system demonstrate that the root mean square errors (RMSEs) in the overlapping areas of panoramic images are no more than 1.0 pixel. In contrast, the RMSEs of the conventional traditional methods are typically more than 6 pixels, and in some cases, even exceed 30 pixels. Moreover, the inverse imaging model has successfully addressed the issue of empty pixels. The proposed method can effectively meet the accurate panoramic imaging requirements for complex surroundings with varied object-distance information.