Robust focal length estimation based on minimal solution method

Deqing Chen, Hang Shao, Qionghai Dai
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引用次数: 1

Abstract

We present a new approach to estimate the focal length for camera calibration in multiview reconstruction. As a popular camera calibration approach, minimal solution method gives rise to a great number of focal-length estimates, from which generating an accurate one is of great significance. Our method concentrates on how to obtain an accurate estimate and is carried out in two steps: firstly, a norm constraint for the fundamental matrix is employed to prune the low-confidence focal-length candidates. Then the focal-length estimate is obtained with a robust focal-length estimation scheme, which consists of occurrence to probability transform, focal-length candidates resample and final estimation with expectation. Experimental results demonstrate that our method could obtain better estimate with both higher accuracy and higher stability than the state-of-the-art method.
基于最小解法的鲁棒焦距估计
提出了一种多视点重建中用于摄像机标定的焦距估计方法。最小解法作为一种常用的摄像机标定方法,会产生大量的焦距估计,从中产生准确的焦距估计具有重要意义。该方法主要研究如何获得准确的估计,并分两步进行:首先,利用基本矩阵的范数约束对低置信度焦距候选者进行修剪;然后采用一种鲁棒焦距估计方案得到焦距估计,该方案由发生-概率变换、候选焦距重采样和最终的期望估计组成。实验结果表明,与现有方法相比,该方法具有更高的估计精度和稳定性。
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