摘要
为了解决汽车周围360°场景重建问题,提出一种适用于车载嵌入式平台的鸟瞰全景图拼接算法,可作为智能汽车环境感知的有效手段.将4个鱼眼摄像头安装于汽车车身,可获得近距离道路环境的图像;采用一种鱼眼图像投影到地面的方法,克服传统方法中存在盲区的问题,同时大大提高计算速度;提出一种基于时域和空域信息的图像融合方法,可以解决摄像机位置差异给拼接造成的困难;为了解决摄像机快速标定问题,采用一种交互式姿态调整方法,运算过程简单,对摄像机安装角度没有精确要求.结果表明,该算法能够实时生成高质量的全景图.
A panoramic image stitching algorithm for embedded system was proposed to reconstruct the 360-degree scene for intelligent vehicles. We used four fish-eye cameras to acquire the images of the near road area. A method of mapping the fish-eye image to the bird's-eye view eliminated the blind spots of the driver with low computational complexity. An image fusion method solved the parallax problem in image stitching by combining time and space-domain information. For convenience of installation and calibration of the cameras, an interactive tunning process was proposed to simplify the installation and make the calibration of extrinsic parameters easy. The experiment results indicate that the proposed method can produce panoramic image with high quality.
出处
《浙江大学学报(工学版)》
EI
CAS
CSCD
北大核心
2014年第2期292-296,共5页
Journal of Zhejiang University:Engineering Science
基金
国家自然科学基金资助项目(60534070
90820306)
关键词
图像拼接
辅助驾驶
摄像机标定
全景图
image stitching; assisted driving; camera calibration; panoramic image