Natural scene synthesis using multiple eigenspaces

Although significant research effort has been devoted to the natural scene analysis, there hasn't been much work on natural scene synthesis. The research of such nature can help to understand the hidden structure of natural texture and the illumination patterns for classification and segmentation purposes. The common texture synthesis methods are not suitable for natural scene synthesis due to inhomogeneity of the natural textures. In this paper, we propose a new natural scene synthesis framework based on multiple eigenspace decomposition, which is a natural extension of principle component analysis (PCA). Two levels of multiple eigenspaces are used; label level multiple eigenspaces for generating depth map and color level multiple eigenspaces for generating nature textures to fill the label maps. Experimental results are presented to show the effectiveness of the proposed framework.