Efficient automatic depth estimation for video

Abstract

Estimating depth in monoscopic images and videos is a non-trivial problem due to the inherent ambiguity that arises when a 3D scene is projected onto a 2D plane (the image). But because depth estimation is so useful, many different techniques have been developed to solve this problem. Unfortunately these methods tend to be computationally intensive or require precise knowledge about the camera that captured the scene. We present a simple and straightforward technique that can estimate relative depth in video sequences using well-established computer vision principles. We also utilize recent advancements in non-linear filtering to make the estimation process computationally efficient. The result produces depth maps comparable to ground truth depths extracted by state-of-the-art estimation methods.