Comprehensive depth estimation algorithm for efficient stereoscopic content creation in three-dimensional video systems

Abstract

Two-dimensional to three-dimensional (3-D) conversion in 3-D video applications has attracted great attention as it can alleviate the problem of stereoscopic content shortage. Depth estimation is an essential part of this conversion since the depth accuracy directly affects the quality of a stereoscopic image. In order to generate a perceptually reasonable depth map, a comprehensive depth estimation algorithm that considers the scenario type is presented. Based on the human visual system mechanism, which is sensitive to a change in the scenario, this study classifies the type of scenario into four classes according to the relationship between the movements of the camera and the object, and then leverages different strategies on the basis of the scenario type. The proposed strategies efficiently extract the depth information from different scenarios. In addition, the depth generation method for a scenario in which there is no motion, neither of the object nor the camera, is also suitable for the single image. Qualitative and quantitative evaluation results demonstrate that the proposed depth estimation algorithm is very effective for generating stereoscopic content and providing a realistic visual experience.