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Reliable frame-to-frame motion estimation for vehicle-mounted surround-view camera systems

机译:车载环视摄像机系统的可靠的逐帧运动估计

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Modern vehicles are often equipped with a surround-view multi-camera system. The current interest in autonomous driving invites the investigation of how to use such systems for a reliable estimation of relative vehicle displacement. Existing camera pose algorithms either work for a single camera, make overly simplified assumptions, are computationally expensive, or simply become degenerate under non-holonomic vehicle motion. In this paper, we introduce a new, reliable solution able to handle all kinds of relative displacements in the plane despite the possibly non-holonomic characteristics. We furthermore introduce a novel two-view optimization scheme which minimizes a geometrically relevant error without relying on 3D point related optimization variables. Our method leads to highly reliable and accurate frame-to-frame visual odometry with a full-size, vehicle-mounted surround-view camera system.
机译:现代车辆通常配备有环视多摄像机系统。当前对自动驾驶的兴趣促使人们对如何使用这种系统进行相对车辆排量的可靠估计进行研究。现有的相机姿态算法要么适用于单个相机,要么进行过分简化的假设,要么计算量大,要么在非完整的车辆运动下变得简陋。在本文中,我们介绍了一种新的,可靠的解决方案,尽管可能具有非完整特性,但该解决方案可以处理平面中的各种相对位移。我们还介绍了一种新颖的两视图优化方案,该方案在不依赖3D点相关优化变量的情况下将几何相关误差最小化。我们的方法可通过全尺寸,车载环视摄像头系统实现高度可靠且精确的逐帧视觉测距。

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