Tracking with Stereo-vision System for Low Speed Following Applications

J. Morat, F. Devernay, S. Cornou
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引用次数: 16

Abstract

Research in adaptative cruise control (ACC) is currently one of the most important topics in the field of intelligent transportation systems. The main challenge is to perceive the environment, especially at low speed. In this paper, we present a novel approach to track the 3D trajectory and speed of the obstacles and the surrounding vehicles through a stereo-vision system. This tracking method extends the classical patch-based Lucas-Kanade algorithm by integrating the geometric constraints of the stereo system into the motion model: the epipolar constraint, which enforces the tracked patches to remain on the epipolar lines, and the magnification constraint, which links the disparity of the tracked patches to the apparent size of these patches. We report experimental results on simulated and real data showing the improvement in accuracy and robustness of our algorithm compared to the classical Lucas-Kanade tracker.
基于立体视觉系统的低速跟踪应用
自适应巡航控制(ACC)是当前智能交通领域的研究热点之一。主要的挑战是感知环境,特别是在低速行驶时。在本文中,我们提出了一种利用立体视觉系统跟踪障碍物和周围车辆的三维轨迹和速度的新方法。该跟踪方法扩展了经典的基于补丁的Lucas-Kanade算法,通过将立体系统的几何约束整合到运动模型中:极面约束(强制跟踪补丁保持在极面线上)和放大约束(将跟踪补丁的视差与这些补丁的视尺寸联系起来)。我们报告了模拟和真实数据的实验结果,表明与经典的Lucas-Kanade跟踪器相比,我们的算法在准确性和鲁棒性方面有所提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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