This paper proposes a novel algorithm of discovering the structure of a kaleidoscopic imaging system that consists of multiple planar mirrors and a camera. The kaleidoscopic imaging system can be recognized as the virtual multi-camera system and has strong advantages in that the virtual cameras are strictly synchronized and have the same intrinsic parameters. In this paper, we focus on the extrinsic calibration of the virtual multi-camera system. The problems to be solved in this paper are two-fold. The first problem is to identify to which mirror chamber each of the 2D projections of mirrored 3D points belongs. The second problem is to estimate all mirror parameters, i.e., normals, and distances of the mirrors. The key contribution of this paper is to propose novel algorithms for these problems using a single 3D point of unknown geometry by utilizing a kaleidoscopic projection constraint, which is an epipolar constraint on mirror reflections. We demonstrate the performance of the proposed algorithm of chamber assignment and estimation of mirror parameters with qualitative and quantitative evaluations using synthesized and real data.
翻译:本文提出了发现由多平面镜像和照相机组成的千兆字面成像系统结构的新奇算法。 千兆字面成像系统可以被确认为虚拟多镜头系统, 并且具有强大的优势, 虚拟相机严格同步, 具有相同的内在参数。 在本文中, 我们集中关注虚拟多镜头系统的外部校准。 本文要解决的问题有两个方面。 第一个问题是确定反射 3D 点的 2D 投影中每个投影属于哪个镜室。 第二个问题是估算所有镜像参数, 即正常值和镜体距离。 本文的关键贡献是通过使用一个单一的3D 点来提出这些问题的新算法, 使用合成和真实数据, 使用未知的3D 点来进行测地测量。 这是对镜像反射的缩影约束。 我们展示了拟议室分配和估计镜像参数的算法, 并用定性和定量评价来使用合成的和真实数据。