Detail publikace

Camera auto-calibration for complex scenes

ALI, A. SMRŽ, P.

Originální název

Camera auto-calibration for complex scenes

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

In this paper, we propose a novel method for automatic camera calibration based on pedestrians' observations. Our proposed method is capable of estimating calibration parameters for complex scenes having more than one ground plane. Unlike existing methods that require time-consuming optimization step, our method uses real-time re-estimation step based on fuzzy logic while relaxing the assumption on the number of ground planes in the scene. Furthermore, we propose a dominant ground plane detection step for better calibration parameter estimation on complex scenes. To evaluate our proposed method, we run comprehensive testing using 5 different datasets covering varieties of calibration parameters and scene properties, we also conduct tests on a synthetic dataset for more detailed analysis.

Klíčová slova

camera auto-calibration, pedestrian detection, pedestrian segmentation, pedestrian tracking, RANSAC, multiple ground planes, fuzzy logic, vanishing points

Autoři

ALI, A.; SMRŽ, P.

Vydáno

15. 3. 2021

Nakladatel

SPIE - the international society for optics and photonics

Místo

Rome

ISBN

978-1-5106-4041-2

Kniha

SPIE 11605

Strany od

1

Strany do

11

Strany počet

11

URL

https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11605/116051W/Camera-auto-calibration-for-complex-scenes/10.1117/12.2586983.full?SSO=1

BibTex

@inproceedings{BUT182943,
  author="Anas {Ali} and Pavel {Smrž}",
  title="Camera auto-calibration for complex scenes",
  booktitle="SPIE 11605",
  year="2021",
  pages="1--11",
  publisher="SPIE - the international society for optics and photonics",
  address="Rome",
  doi="10.1117/12.2586983",
  isbn="978-1-5106-4041-2",
  url="https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11605/116051W/Camera-auto-calibration-for-complex-scenes/10.1117/12.2586983.full?SSO=1"
}