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Visual odometry with unsynchronized multi-cameras setup for intelligent vehicle application

机译:具有非同步多摄像机设置的视觉里程表,可用于智能车辆应用

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This paper presents a visual odometry with metric scale estimation of a multi-camera system in challenging un-synchronized setup. The intended application is in the field of intelligent vehicles. We propose a new algorithm named “triangle-based” method. The proposed algorithm employs the information from both extrinsic and intrinsic parameters of calibrated cameras. We assume that the trajectory between two consecutive frames of a camera is a linear segment (straight trajectory). The relative camera poses are estimated via classical Structure-from-Motion. Then, the scale factors are computed by imposing the known extrinsic parameters and the linearity assumption. We verify the validity of our method both in simulated and real conditions. For the real world, the motion trajectory estimated for image sequence of two cameras from KITTI dataset is compared against the GPS/INS ground truth.
机译:本文提出了一种具有挑战性的非同步设置的多相机系统的视觉里程表,具有公制比例尺估计。预期的应用是在智能车辆领域。我们提出了一种新的算法,称为“基于三角形的”方法。所提出的算法利用了来自校准相机的外部参数和固有参数的信息。我们假设摄像机的两个连续帧之间的轨迹是线性段(直线轨迹)。摄像机的相对姿态是通过经典的“动感结构”估算的。然后,通过施加已知的外部参数和线性假设来计算比例因子。我们在模拟和真实条件下都验证了我们方法的有效性。对于现实世界,将从KITTI数据集中为两个摄像机的图像序列估算的运动轨迹与GPS / INS地面真实情况进行比较。

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