3D Room Reconstruction from A Single Fisheye Image

We propose a rapid and accurate approach to recover the layout of a room automatically from a single fisheye image. It decomposes the fisheye image to a set of perspective images and jointly extract line images from the fisheye image and perspective images for geometric information. The semantic information gained from semantic segmentation on a cylinder expansion of the fisheye image are then used for structure line determination. By considering distinct features contained in the perspective images, the invalid hypotheses are filtered effectively and the most accurate structure lines are selected to minimize computational cost. To evaluate the effectiveness of the proposed approach, we construct an annotated fisheye image dataset. Comprehensive experimental evaluation on the dataset illustrate that our proposed approach produces higher quality layout estimations than existing layout reconstruction approaches and being 6 times faster in the reconstruction time.