AD efficient synthesis approach for perspective distorted textures

In image-based rendering (IBR), it is commonly employed textures which extracted from reality onto virtual worlds to synthesize novel views, and the patch-based sampling has proven superior in complexity and synthesis quality. However, the conventional synthesis approaches can not be applied directly to the texture which is captured by camera with perspective-like projection, because such textures content have unequal object scale from near to far (perspective distorted textures). In this paper, we develop an automatic and effective approach to synthesize the structured textures with perspective distorted property. The idea behind the work is that the structured textures generally have significant line composition. Therefore, we extract all possible variations from distorted texture as parameterized shapes in binary image, and the Hough transform is applied to detect all possible line structures, and the set of main control points can be identified through Hough transform for planar reconstruction. Experimental results indicated that the proposed texture synthesis algorithm can achieve surprising visual quality for various perspective distorted textures.