Real-time 3D reconstruction of traffic scenes under an images-to-model framework

Abstract

Timely extraction and intuitive display of vehicle information are two challenges for intelligent traffic surveillance. This paper presents a system for real-time 3D reconstruction of traffic scenes from video frames. We first propose a images-to-model (I2M) framework for images based 3D modeling. Under this framework, we take the traffic scene model apart into the static background model and dynamic vehicle models. Compared to the conventional multi-view stereo methods for object reconstruction, we design a scheme, which uses combination of vehicle information extraction and vehicle model retrieval, to reconstruct the moving vehicles in real-time. We further study how to integrate the retrieved vehicle models into the static background model to generate the desired traffic scene model. We also evaluate our system using three real traffic scenes, and the experimental results show that our proposed methods are effective.