Self-calibration of spherical rectification for a PTZ-stereo system

Since PTZ (pan–tilt–zoom) camera is able to obtain multi-view-angle and multi-resolution information, PTZ-stereo system using two PTZ cameras has much higher capability and flexibility compared with traditional stereo system. In this paper, we propose a self-calibration framework to deal with the calibration of spherical rectification, which can be deemed as a kind of relative pose estimation, for a PTZ-stereo system. The goal of this calibration is to guarantee high performance of stereo rectification, so that stereo matching can be achieved more efficiently and accurately. In this framework, we assume two PTZ cameras are fully calibrated, i.e., the focal length and the local camera orientation can be computed by given pan–tilt–zoom values. This approach, which is based on point matches, aims at finding uniformly distributed point matches in an iterative way. At each iteration, according to the distribution of previously used point matches, the system could automatically guide two cameras to move to collect a new match. Point matching is firstly performed for the lowest zoom setting (widest field of view). Once a candidate match is chosen, each camera is then controlled to zoom in on corresponding point to get a refined match with high spatial resolution. The final match will be added into the estimation to update the calibration parameters. Compared with previous researches, the proposed framework has the following advantages: (1) Neither manual interaction nor calibration object is needed. Calibration samples (point matches) will be added and removed in each stage automatically. (2) The distribution of calibration samples is as uniform as possible so that biased estimation could be avoided to some extent. (3) The accuracy of calibration can be controlled and improved when iteration goes on. These advantages make the proposed framework more practicable in applications. Experimental results illustrate its accuracy.