Slant estimation for active vision using edge directions in omnidirectional images

In this paper, we propose a novel method to estimate the slant of omnidirectional image sensors which can acquire images of an environment with a FOV close to 360° × 180°. The proposed method consists of two steps: a low resolution voting followed by a least squares method (LSM). First, the direction of each edge pixel in the omnidirectional image is computed and projected to the plane of Z = 1. The biggest peak formed by the vertical edges, which are prevalent in indoor and urban scenes, is detected. Then, edge directions whose projections to the voting plane pass near the peak are used to estimate the slant of the sensor by LSM. Experimental results in a real environment show the effectiveness of the proposed method.