Depth from a Single Image through User Interaction
In this paper we present a method to obtain a depth map from a single image of a scene by exploiting both image content and user interaction. Assuming that regions with low gradients will have similar depth values, we formulate the problem as an optimization process across a graph, where pixels are considered as nodes and edges between neighbouring pixels are assigned weights based on the image gradient. Starting from a number of user- defined constraints, depth values are propagated between highly connected nodes i.e. with small gradients. Such constraints include, for example, depth equalities and inequalities between pairs of pixels, and may include some information about perspective. This framework provides a depth map of the scene, which is useful for a number of applications.
Angeles Lopez, Elena Garces, and Diego Gutierrez. "Depth from a Single Image through User Interaction". CEIG - Spanish Computer Graphics Conference, 1-10, 2014.