2D-to-3D stereoscopic conversion: depth-map estimation in a 2D single-view image

Abstract

With increasing demands of 3D contents, conversion of many existing two-dimensional contents to three-dimensional contents has gained wide interest in 3D image processing. It is important to estimate the relative depth map in a single-view image for the 2D-To-3D conversion technique. In this paper, we propose an automatic conversion method that estimates the depth information of a single-view image based on degree of focus of segmented regions and then generates a stereoscopic image. Firstly, we conduct image segmentation to partition an image into homogeneous regions. Then, we construct a higher-order statistics (HOS) map, which represents the spatial distribution of high-frequency components of the input image. the HOS is known to be well suited for solving detection and classification problems because it can suppress Gaussian noise and preserve some of non-Gaussian information. We can estimate a relative depth map with these two cues and then refine the depth map by post-processing. Finally, a stereoscopic image is generated by calculating the parallax values of each region using the generated depth-map and the input image.