Rough compressed domain camera pose estimation through object motion

We present an unsupervised method to estimate the camera orientation angle on monocular video scenes in the H.264 compressed domain. The method is based on the presence of moving objects in the scene. We start by estimating the global camera motion based on the motion vectors present in the stream, detect and track moving objects and estimate their relative distance to the camera by analyzing the temporal evolution of the objects' dimensions. The evolution of the motion compensated, vertical positions of key points within moving objects are used to infer the extrinsic orientation angle of the camera.