Efficient and Accurate Stitching for 360° Dual-Fisheye Images and Videos.

Back-to-back dual-fisheye cameras are the most cost-effective devices to capture 360° visual content. However, image and video stitching for such cameras often suffer from the effect of fisheye distortion, photometric inconsistency between the two views, and non-collocated optical centers. In this paper, we present algorithms for geometric calibration, photometric compensation, and seamless stitching to address these issues for back-to-back dual-fisheye cameras. Specifically, we develop a co-centric trajectory model for geometric calibration to characterize both intrinsic and extrinsic parameters of the fisheye camera to fifth-order precision, a photometric correction model for intensity and color compensation to provide efficient and accurate local color transfer, and a mesh deformation model along with an adaptive seam carving method for image stitching to reduce geometric distortion and ensure optimal spatiotemporal alignment. The stitching algorithm and the compensation algorithm can run efficiently for 1920×960 images. Quantitative evaluation of geometric distortion, color discontinuity, jitter, and ghost artifact of the resulting image and video shows that our solution outperforms the state-of-the-art techniques.