论文标题
Fisheye视频序列的运动估计结合透视投影与摄像机校准信息
Motion estimation for fisheye video sequences combining perspective projection with camera calibration information
论文作者
论文摘要
Fisheye摄像机在监视和汽车应用中证明了一种方便的手段，因为它们为捕捉周围环境提供了广阔的视野。但是，与典型的直线图像相反，Fisheye视频序列遵循从世界坐标到图像平面的不同映射，而标准视频处理技术中未考虑的图像平面。在本文中，我们通过将视角投影与有关基础鱼眼投影的知识相结合，为真实世界的鱼眼视频提供了运动估计方法。后者是通过摄像机校准获得的，因为实际镜头很少遵循精确的模型。此外，我们引入了一个超宽角度的重新映射，否则将导致Fisheye边界的运动补偿结果错误。这两个概念都扩展了现有的混合运动估计方法，用于以基于块的方式在传统和鱼眼匹配之间决定传统和鱼眼之间的视频序列。与该方法相比，针对现实世界中的fisheye视频序列，提出的校准和重新映射扩展在亮度PSNR中的增益高达0.58 dB。与传统的块匹配相比，总体上涨高达3.32 dB。
Fisheye cameras prove a convenient means in surveillance and automotive applications as they provide a very wide field of view for capturing their surroundings. Contrary to typical rectilinear imagery, however, fisheye video sequences follow a different mapping from the world coordinates to the image plane which is not considered in standard video processing techniques. In this paper, we present a motion estimation method for real-world fisheye videos by combining perspective projection with knowledge about the underlying fisheye projection. The latter is obtained by camera calibration since actual lenses rarely follow exact models. Furthermore, we introduce a re-mapping for ultra-wide angles which would otherwise lead to wrong motion compensation results for the fisheye boundary. Both concepts extend an existing hybrid motion estimation method for equisolid fisheye video sequences that decides between traditional and fisheye block matching in a block-based manner. Compared to that method, the proposed calibration and re-mapping extensions yield gains of up to 0.58 dB in luminance PSNR for real-world fisheye video sequences. Overall gains amount to up to 3.32 dB compared to traditional block matching.
