Traffic Surveillance Camera Calibration by 3D Model Bounding Box Alignment for Accurate Vehicle Speed Measurement

Abstract

In this paper, we focus on fully automatic traffic surveillance camera calibration, which we use for speed measurement of passing vehicles. We improve over a recent state-of-the-art camera calibration method for traffic surveillance based on two detected vanishing points. More importantly, we propose a novel automatic scene scale inference method. The method is based on matching bounding boxes of rendered 3D models of vehicles with detected bounding boxes in the image. The proposed method can be used from arbitrary viewpoints, since it has no constraints on camera placement. We evaluate our method on the recent comprehensive dataset for speed measurement BrnoCompSpeed. Experiments show that our automatic camera calibration method by detection of two vanishing points reduces error by 50% (mean distance ratio error reduced from 0.18 to 0.09) compared to the previous state-of-the-art method. We also show that our scene scale inference method is more precise, outperforming both state-of-the-art automatic calibration method for speed measurement (error reduction by 86% -- 7.98km/h to 1.10km/h) and manual calibration (error reduction by 19% -- 1.35km/h to 1.10km/h). We also present qualitative results of the proposed automatic camera calibration method on video sequences obtained from real surveillance cameras in various places, and under different lighting conditions (night, dawn, day).

accepted to CVIU

References in corpus (2)

• Fully Convolutional Networks for Semantic Segmentation
• Object Contour Detection with a Fully Convolutional Encoder-Decoder Network

Cited by in corpus (10)

• Vision-based Vehicle Speed Estimation: A Survey
• Detection of 3D Bounding Boxes of Vehicles Using Perspective Transformation for Accurate Speed Measurement
• Camera Calibration with Pose Guidance
• Efficient Vision-based Vehicle Speed Estimation
• Extrinsic Infrastructure Calibration Using the Hand-Eye Robot-World Formulation
• Training-free Monocular 3D Event Detection System for Traffic Surveillance
• Maximum Likelihood Speed Estimation of Moving Objects in Video Signals
• CAROM -- Vehicle Localization and Traffic Scene Reconstruction from Monocular Cameras on Road Infrastructures
• Traffic Danger Recognition With Surveillance Cameras Without Training Data
• Traffic Camera Calibration via Vehicle Vanishing Point Detection