基于监督学习的单幅图像深度估计综述

Depth estimation from a single image is an important technology in the image-based depth acquisition for 3D reconstruction, which is also a classical problem in computer vision. Recently, supervised learning based depth es-timation from a single image develops rapidly. In this paper, the recent related literatures are reviewed and super-vised learning based depth estimation from a single image and its model and optimization are introduced. The current research situations of the parametric learning method, non-parametric learning method and deep learning method both in domestic and abroad are analyzed respectively with their advantages and disadvantages. At last, summarizing these methods leads to the conclusion that depth estimation from a single image in deep learning framework is the development trend and research priority in the future.