3D Bounding Box Estimation for Autonomous Vehicles by Cascaded Geometric Constraints and Depurated 2D Detections Using 3D Results

Understand

3D object detection is one of the most important tasks in 3D vision perceptual system of autonomous vehicles.

• In this paper, we propose a novel two stage 3D object detection method aimed at get the optimal solution of object location in 3D space based on regressing two additional 3D object properties by a deep convolutional neural network and combined with cascaded geometric constraints between the 2D and 3D boxes.
• First, we modify the existing 3D properties regressing network by adding two additional components, viewpoints classification and the center projection of the 3D bounding box s bottom face.
• Second, we use the predicted center projection combined with similar triangle constraint to acquire an initial 3D bounding box by a closed-form solution.