Recovering depth of a dynamic scene using real world motion prior
Given a video of a dynamic scene captured using a dynamic camera, we present a method to recover a dense depth map of the scene with a focus on estimating the depth of the dynamic objects. We assume that the static portions of the scene help estimate the pose of the cameras. We recover a dense depth map of the scene via a plane sweep stereo approach. The relative motion of the dynamic object in the scene however, results in an inaccurate depth estimate. Estimating the accurate depth of the dynamic object is an ambiguous problem since both the depth and the real world speed of the object are unknown. In this work, we show that by using occlusions and putting constraints on the speed of the object we can bound the depth of the object. We can then incorporate this real world motion into the plane sweep stereo framework to obtain a more accurate depth for the dynamic object. We focus on videos with people walking in the scene and show the effectiveness of our approach through quantitative and qualitative results.