  This paper as technology report is focusing on evaluation and performance
about depth estimations based on lidar data and stereo images(front left and
front right). The lidar 3d cloud data and stereo images are provided by ford.
In addition, this paper also will explain some details about optimization for
depth estimation performance. And some reasons why not use machine learning to
do depth estimation, replaced by pure mathmatics to do stereo depth estimation.
The structure of this paper is made of by following:(1) Performance: to discuss
and evaluate about depth maps created from stereo images and 3D cloud points,
and relationships analysis for alignment and errors;(2) Depth estimation by
stereo images: to explain the methods about how to use stereo images to
estimate depth;(3)Depth estimation by lidar: to explain the methods about how
to use 3d cloud datas to estimate depth;In summary, this report is mainly to
show the performance of depth maps and their approaches, analysis for them.
