Monocular depth estimation by two-frame triangulation using flat surface constraints

Abstract

Fast and accurate depth estimation is essential for autonomous driving vehicles and autonomous robots. Monocular cameras have been expected to be widely applied due to their lower cost, but since they can't provide depth directly, fast and accurate monocular depth estimation methods are required. This paper proposes a novel method of monocular depth estimation based on flat surface using feature triangulation and two frames per estimation. Experiments under ideal conditions and with the KITTI Vision Benchmark Suite showed that the method achieved smaller errors comparing to existing methods that rely on inertial sensors and many frames.