Abstract: The large-scale smart driving scene reconstruction can feedback the surrounding road traffic environment information for the vehicle control system in the vehicle driving environment,and realize the visualization of the environmental information.At present,the existing three-dimensional reconstruction scheme is mainly oriented to thestructuredscene,and it is difficult to meet the real-time performance required by the smart driving system while ensuring a certain precision which can make when the three-dimensional reconstruction of the large-scale unstructured smart driving scene is performed.In order to solve this problem,a three-dimensional scene reconstruction method based on binocular vision is proposed.Firstly,by optimizing the stereo matching strategy,the stereo matching efficiency is improved,and then the uniform distance feature point extraction algorithm RSD is proposed to reduce the time consumption of 3D point cloud computing and triangulation,and the real-time performance of large-scale smart driving scene reconstruction is improved.The experimental results prove the effectiveness of this algorithm,which can be used to reconstruct the scene of large-scale smart driving scene,and can meet the demand of intelligent driving system in real-time.

Key words: Binocular vision, Depth value calculation, Feature extraction, Intelligent driving scene reconstruction, Stereo matching