Fully Automatic Horizon Estimation for Surveillance Cameras

摘要

This paper deals with automatic estimation of the horizon in videos from fixed surveillance cameras. The proposed algorithm is fully automatic in the sense that no user input is needed per-camera and it works with various scenes (indoor, outdoor, traffic, pedestrian, livestock, etc.). The algorithm detects moving objects, tracks them in time, assesses some of their geometric properties related to the object dimensions and infers observations related to the position of the horizon. We collected a dataset of 47 public camera streams observing suitable scenes of various nature. We annotated ground truth horizons based on geometric properties in the images and by direct human input. We evaluate the proposed algorithm and compare it to human guesses - it turns out that the algorithm is on par with humans or it outperforms them in the difficult scenes.