Most approaches to camera calibration rely on calibration targets of well-known geometry. During data acquisition, calibration target and camera system are typically moved w.r.t. each other, to allow image coverage and perspective versatility. We show that moving the target can lead to small temporary deformations of the target, which can introduce significant errors into the calibration result. While static inaccuracies of calibration targets have been addressed in previous works, to our knowledge, none of the existing approaches can capture time-varying, dynamic deformations. To achieve high-accuracy calibrations despite moving the target, we propose a way to explicitly model dynamic target deformations in camera calibration. This is achieved by using a low-dimensional deformation model with only few parameters per image, which can be optimized jointly with target poses and intrinsics. We demonstrate the effectiveness of modeling dynamic deformations using different calibration targets and show its significance in a structure-from-motion application.
翻译:相机校准的大多数方法都依赖于众所周知的几何校准目标。 在数据采集过程中,校准目标与相机系统一般会相互移动, 以允许图像覆盖和视角多功能性。 我们显示, 移动目标可能导致目标的小型暂时变形, 从而在校准结果中引入重大错误。 虽然在先前的工程中, 据我们所知, 校准目标的静态不准确性已经解决了, 但根据我们的知识, 现有的方法中没有一个能够捕捉时间变异、 动态变形。 尽管移动目标, 要实现高精确度校准, 我们建议一种方法, 在相机校准中明确模拟动态目标变形。 这是通过使用一个低维变形模型实现的, 每图像中只有少量参数, 与目标的成形和内含物一起优化。 我们展示了使用不同的校准目标进行动态变形模型的功效, 并在结构- 移动应用中显示其重要性 。