Depth Transfer: Depth Extraction from Videos Using Nonparametric Sampling
In this chapter, a technique that automatically generates plausible depth maps from videos using nonparametric depth sampling is discussed. We demonstrate this method in cases where existing methods fail (nontranslating cameras and dynamic scenes) This technique is applicable to single images as well as videos. For videos, local motion cues are used to improve the inferred depth maps, while optical flow is used to ensure temporal depth consistency. For training and evaluation, a Microsoft Kinect based system is developed to collect a large dataset containing stereoscopic videos with known depths, and this depth estimation technique outperforms the state of the art on benchmark databases. This method can be used to automatically convert a monoscopic video into stereo for 3D visualization demonstrated through a variety of visually pleasing results for indoor and outdoor scenes, including results from the feature film Charade.