Omnidirectional Depth Recovery based on a Novel Stereo Sensor

Abstract

Omnidirectional depth map generation is very important for mobile robot navigation and action planning. In this paper, we present design of a novel stereo sensor and an algorithm to recovery dense 3D depth map for a mobile robot. The vision system is composed of a perspective camera and two hyperbolic mirrors. Once the system has been calibrated and two image points respectively projected by upper and nether mirrors are matched, the 3D coordinate of the space point can be acquired by means of triangulation. Our method can be divided into two steps. An initial depth map can be calculated using efficient dynamic programming technique. We adopt graph cut algorithm in the second step. With a relatively good initial map, the process of graph cut converges very fast. We also show the necessary modification to handle panoramic images, including deformed matching template, adaptable template scale. Experiment shows that this proposed vision system is feasible as a practical stereo sensor for accurate 3D map generation.