Combining Object Detection and Binocular Vision for 3D Car Pose Estimation

With the rapid development of urban construction,the demand for vehicles is increasing day by day,which brings the demand for automatic driving technology.In order to enhance the ability of the automatic driving system to handle the information about vehicles on road,this paper proposes a car pose estimation method.The method firstly uses the object detection algorithm based on deep-learning to obtain the information of the vehicle on two-dimensional image,and then combines the depth camera with binocular vision to capture the three-dimensional spatial information of the key points of the vehicle;the 3D coordinates are built by integrating the 2D and 3D information which are used to obtain the 3D bounding box of the vehicle,the 3D bounding box could be benefit for distinguishing the car’s spatial orientation in automatic driving system.The method is an end-to-end method without any additional input,and the result can be displayed on the camera in real time.The experimental result shows that the method has a fine recognition effect for the parking lots on road and has a good auxiliary effect on the automatic driving system;the accuracy of the method is also demonstrated by comparing with the existing method.