Reliable depth map regeneration via a novel omnidirectional stereo sensor

Authors:
Lei He;Chuanjiang Luo;Yanfeng Geng;Feng Zhu;Yingming Hao
Affiliations:
Graduate School of Chinese Academy of Sciences, Beijing, China and Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China;Graduate School of Chinese Academy of Sciences, Beijing, China and Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China;Graduate School of Chinese Academy of Sciences, Beijing, China and Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China;Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China;Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
Venue:
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
Year:
2007

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Abstract

We present a method to obtain dense 3D maps for a mobile robot that is equipped with a novel omnidirectional stereo vision sensor. The vision sensor 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. To satisfy the reliability requirement by mobile robot navigation, we use high-quality stereo matching algorithm - the graph cut method. An initial depth map can be calculated using efficient dynamic programming technique. With a relatively good initial map, the process of graph cut converges quickly. 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.