2D-to-3D conversion is one of the important ways to alleviate the lack of 3D content

in which the key technique is depth estimation from a single image.A depth extraction method based on weighted SIFT flow depth transferring and energy model optimization is proposed.First

k-nearest neighbor images were retrieved by evaluating the global image descriptors between the target image and the images from the RGBD database.Then

pixels of the target image and pixels of its neighbors in the database were matched using SIFT flow

which also generated matching errors used to determine the transferring weights of the neighbors.Next

depth maps of neighboring images were transferred to the target image according to the pixel matching and the transferring weights.The final depth map was obtained by depth refinement based on an energy model.Experimental results show that our scheme can significantly reduce the average relative error and improve the uniformity of the depth map.