Publication detail

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

SOCHOR, J. JURÁNEK, R. HEROUT, A.

Original Title

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

English Title

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

Type

journal article in Web of Science

Language

en

Original 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).

English 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).

Keywords

camera calibration; fully automatic; traffic surveillance; bounding box alignment; vanishing point detection

Released

01.06.2017

Publisher

NEUVEDEN

Location

NEUVEDEN

ISBN

1077-3142

Periodical

COMPUTER VISION AND IMAGE UNDERSTANDING

Year of study

2017

Number

161

State

US

Pages from

87

Pages to

98

Pages count

12

URL

Documents

BibTex


@article{BUT144444,
  author="Jakub {Sochor} and Roman {Juránek} and Adam {Herout}",
  title="Traffic Surveillance Camera Calibration by 3D Model Bounding Box Alignment for Accurate Vehicle Speed Measurement",
  annote="
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).",
  address="NEUVEDEN",
  chapter="144444",
  doi="10.1016/j.cviu.2017.05.015",
  edition="NEUVEDEN",
  howpublished="print",
  institution="NEUVEDEN",
  number="161",
  volume="2017",
  year="2017",
  month="june",
  pages="87--98",
  publisher="NEUVEDEN",
  type="journal article in Web of Science"
}