Estimating structure of indoor scene from a single full-view image

Hanchao Jia, Shigang Li

Abstract: In this paper we propose a novel method of estimating indoor scenes from a single full-view image. On the one hand, the conventional methods cope with limited field of view images, such as perspective images and hemispherical omnidirectional images, which result in visually open boundary condition, called open geometry. On the other hand, a full-view image results in a visually close boundary condition, called close geometry. In this paper we employ the characteristics of close geometry to explore indoor scene understanding from a single full-view image. The proposed close geometry is tested in comparison with the conventional open geometry. The comparative experiment is also carried out between the proposed method and the state-of-the-art method [13]. The experimental results show that the proposed approach can achieve a better performance, and imply that close geometry plays an important role on the interpretation of indoor scenes.