Online Correction of Camera Poses for the Surround-view System: A Sparse Direct Approach
Online Correction of Camera Poses for the Surround-view System: A Sparse Direct Approach
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DOI：
10.1145/3505252
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发表时间：
2022-11-01
影响因子：
5.1
通讯作者：
Zhou，Yicong
中科院分区：
文献类型：
--
作者：
Zhang，Tianjun;Deng，Hao;Zhou，Yicong
全景模块是现代先进驾驶辅助系统不可或缺的组成部分。通过精确地校准环绕视图相机的本征和外征，可以从原始鱼眼图像生成自顶向下的环绕视图。然而，这些相机的姿势有时可能会改变。目前，如何在不重新标定的情况下在线校正全景系统中摄像机的位姿仍然是一个悬而未决的问题。为了解决这个问题，我们引入了稀疏直接框架，并提出了一种新的级联结构的优化方案。该方案实际上是由两个层次的优化和两个相应的光度误差为基础的模型提出。第一级优化的模型称为地面模型，因为其光度误差是在地平面上测量的。对于优化的第二级，它基于所谓的地面相机模型，其中在成像平面上计算光度误差。有了这些模型，姿势校正任务被制定为一个非线性最小二乘问题，以尽量减少相邻的鸟瞰图像重叠区域的光度误差。通过这两个优化层次的级联结构，可以实现速度和精度之间的适当平衡。实验结果表明，该方法可以有效地消除环视系统中摄像机姿态变化引起的错位。源代码和测试用例可在www.example.com上在线获得。
The surround-view module is an indispensable component of a modern advanced driving assistance system. By calibrating the intrinsics and extrinsics of the surround-view cameras accurately, a top-down surround-view can be generated from raw fisheye images. However, poses of these cameras sometimes may change. At present, how to correct poses of cameras in a surround-view system online without re-calibration is still an open issue. To settle this problem, we introduce the sparse direct framework and propose a novel optimization scheme of a cascade structure. This scheme is actually composed of two levels of optimization and two corresponding photometric error based models are proposed. The model for the first-level optimization is called the ground model, as its photometric errors are measured on the ground plane. For the second level of the optimization, it’s based on the so-called ground-camera model, in which photometric errors are computed on the imaging planes. With these models, the pose correction task is formulated as a nonlinear least-squares problem to minimize photometric errors in overlapping regions of adjacent bird’s-eye-view images. With a cascade structure of these two levels of optimization, an appropriate balance between the speed and the accuracy can be achieved. Experiments show that our method can effectively eliminate the misalignment caused by cameras’ moderate pose changes in the surround-view system. Source code and test cases are available online at https://cslinzhang.github.io/CamPoseCorrection/.