驾驶员辅助系统的增强运动估计。弯曲道路模型的集成

Gregor Schewior, H. Blume
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引用次数: 2

摘要

本文提出了一种扩展的基于模型的运动矢量场改进方法。通过对弯曲道路模型的集成,利用基于预测分块的运动估计器对车载前置摄像头捕获的视频信号进行估计,从而显著提高了运动矢量场的质量。优化步骤是通过对典型驾驶场景的合成运动矢量场进行建模,在迭代步骤中作为附加运动矢量候选者进行优化。所提出的增强方法对各种驾驶情况都有效,在客观和主观性能方面都有显著改善,同时只需要较低的计算开销。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced motion estimation for driver assistance systems — Integration of a curved road model
This paper presents an extended efficient modelbased approach for the improvement of motion vector fields for driver assistance systems. Through the integration of a curved road model the quality of motion vector fields, estimated by a predictive block-based motion estimator working on video signals which are captured by a front camera inside a car, is significantly increased. The optimization step is performed by modeling synthetic motion vector fields of typical driving scenes acting in an iterative step as additional motion vector candidates. The proposed enhanced approach which is effective for all kinds of driving situations provides a significant improvement in terms of objective and subjective performance while requiring only low computational overhead.
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