Towards A New Generation of Car Navigation System - Data Fusion Technology in Solving On-board Camera Registration Problem
Towards A New Generation of Car Navigation System - Data Fusion Technology in Solving On-board Camera Registration Problem
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迈向新一代汽车导航系统——数据融合技术解决车载摄像头配准问题
DOI：
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发表时间：
2004
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通讯作者：
Zhencheng Hu
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作者：
Zhencheng Hu
为了在增强现实（AR）空间中正确地对齐真实的和虚拟世界中的对象，必须保持跟踪摄像机的精确3D位置和方向，这被称为摄像机配准问题。传统的基于视觉或惯性传感器的解决方案大多是为结构良好的环境而设计的，然而，这对于户外不受控制的道路导航应用是不可用的。提出了一种结合视觉、GPS和三维惯性陀螺技术的混合式摄像机位姿跟踪系统。融合方法是基于我们的PMM（参数化模型匹配）算法，其中的道路形状模型是从数字地图参考GPS绝对道路位置，并与道路特征提取的真实的图像匹配。惯性数据估计初始可能的运动，并且还用作稳定输出的相对公差。通过不同路况和道路类型的真实的道路试验，对本文提出的算法进行了验证。
To properly align objects in the real and virtual world in an Augmented Reality (AR) space, it is essential to keep tracking camera’s exact 3D position and orientation, which is well known as the camera registration problem. Traditional vision based or inertial sensor based solutions are mostly designed for well-structured environment, which is however unavailable for outdoor uncontrolled road navigation applications. This paper proposed a hybrid camera pose tracking system that combines vision, GPS and 3D inertial gyroscope technologies. The fusion approach is based on our PMM (parameterized model matching) algorithm, in which the road shape model is derived from the digital map referring to GPS absolute road position, and matches with road features extracted from the real image. Inertial data estimates the initial possible motion, and also serves as the relative tolerance to stabilize output. The algorithms proposed in this paper are validated with the experimental results of real road tests under different conditions and types of road.