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Autocalib: automatic traffic camera calibration at scale

Authors:

Romil Bhardwaj,

Gopi Krishna Tummala,

Ganesan Ramalingam,

Ramachandran Ramjee,

Prasun SinhaAuthors Info & Claims

BuildSys '17: Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments

Article No.: 14, Pages 1 - 10

https://doi.org/10.1145/3137133.3137149

Published: 08 November 2017 Publication History

Abstract

Emerging smart cities are typically equipped with thousands of outdoor cameras. However, these cameras are typically not calibrated, i.e., information such as their precise mounting height and orientation is not available. Calibrating these cameras allows measurement of real-world distances from the video, thereby, enabling a wide range of novel applications such as identifying speeding vehicles, city road planning, etc. Unfortunately, robust camera calibration is a manual process today and is not scalable.

In this paper, we propose AutoCalib, a system for scalable, automatic calibration of traffic cameras. AutoCalib exploits deep learning to extract selected key-point features from car images in the video and uses a novel filtering and aggregation algorithm to automatically produce a robust estimate of the camera calibration parameters from just hundreds of samples. We have implemented AutoCalib as a service on Azure that takes in a video segment and outputs the camera calibration parameters. Using video from real-world traffic cameras, we show that AutoCalib is able to estimate real-world distances with an error of less than 12%.

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Cited By

Li YZhao ZChen YZhang XTian R(2023)Automatic Roadside Camera Calibration with TransformersSensors10.3390/s2323952723:23(9527)Online publication date: 30-Nov-2023
https://doi.org/10.3390/s23239527
Bartl VŠpaňhel JDobeš PJuránek RHerout A(2020)Automatic camera calibration by landmarks on rigid objectsMachine Vision and Applications10.1007/s00138-020-01125-x32:1Online publication date: 6-Oct-2020
https://doi.org/10.1007/s00138-020-01125-x
Bejarano GKulkarni ARaushan RSeetharam ARamesh A(2019)SWaPProceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3360322.3360846(233-242)Online publication date: 13-Nov-2019
https://dl.acm.org/doi/10.1145/3360322.3360846
Show More Cited By

Index Terms

Autocalib: automatic traffic camera calibration at scale
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Sensor networks

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Autocalib: automatic traffic camera calibration at scale
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Published In

cover image ACM Conferences

BuildSys '17: Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments

November 2017

292 pages

ISBN:9781450355445

DOI:10.1145/3137133

General Chair:
Kamin Whitehouse
University of Virginia
,
Program Chairs:
Prabal Dutta
University of California, Berkeley
,
Hae Young Noh
Carnegie Mellon University

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 08 November 2017

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BuildSys '17

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BuildSys '17: The 4th ACM International Conference on Systems for Energy-Efficient Built Environments

November 8 - 9, 2017

Delft, Netherlands

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Overall Acceptance Rate 148 of 500 submissions, 30%

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Cited By

Li YZhao ZChen YZhang XTian R(2023)Automatic Roadside Camera Calibration with TransformersSensors10.3390/s2323952723:23(9527)Online publication date: 30-Nov-2023
https://doi.org/10.3390/s23239527
Bartl VŠpaňhel JDobeš PJuránek RHerout A(2020)Automatic camera calibration by landmarks on rigid objectsMachine Vision and Applications10.1007/s00138-020-01125-x32:1Online publication date: 6-Oct-2020
https://doi.org/10.1007/s00138-020-01125-x
Bejarano GKulkarni ARaushan RSeetharam ARamesh A(2019)SWaPProceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3360322.3360846(233-242)Online publication date: 13-Nov-2019
https://dl.acm.org/doi/10.1145/3360322.3360846
Tummala GDas TSinha PRamnath REskicioglu RMottola LPriyantha B(2019)SmartDashCamProceedings of the 18th International Conference on Information Processing in Sensor Networks10.1145/3302506.3310397(157-168)Online publication date: 16-Apr-2019
https://dl.acm.org/doi/10.1145/3302506.3310397
Bhardwaj RTummala GRamalingam GRamjee RSinha P(2018)AutoCalibACM Transactions on Sensor Networks10.1145/319966714:3-4(1-27)Online publication date: 27-Nov-2018
https://dl.acm.org/doi/10.1145/3199667
Bhardwaj RTummala GRamalingam GRamjee RSinha PWhitehouse KDutta PNoh H(2017)AutocalibProceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments10.1145/3137133.3141434(1-2)Online publication date: 8-Nov-2017
https://dl.acm.org/doi/10.1145/3137133.3141434

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