A new strategy for improving vision based tracking accuracy based on utilization of camera calibration information

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Camera calibration is one of the essential components of a vision based tracking system where the objective is to extract three dimensional information from a set of two dimensional frames. The information extracted from the calibration process is significant for examining the accuracy of the vision sensor, and thus further for estimating its effectiveness as a tracking system in real applications. This paper introduces another use for this information in which the proper location of the camera can be predicted. Anew mathematical formula based on utilizing the extracted calibration information was used for finding the optimum location for the camera, which provides the best detection accuracy. Moreover, the calibration information was also used for selecting the proper image Denoising filter. The results obtained proved the validity of the proposed formula in finding the desired camera location where the smallest detection errors can be produced. Also, results showed that the proper selection of the filter parameters led to a considerable enhancement in the overall accuracy of the camera, reducing the overall detection error by 0.2 mm.

LanguageEnglish
Title of host publication22nd International Conference on Automation and Computing
Subtitle of host publicationICAC 2016: Tackling the New Challenges in Automation and Computing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Chapter3
Pages278-283
Number of pages6
ISBN (Electronic)9781862181311
DOIs
Publication statusE-pub ahead of print - 24 Oct 2016
Event22nd International Conference on Automation and Computing - Colchester, United Kingdom
Duration: 7 Sep 20168 Sep 2016
Conference number: 22

Conference

Conference22nd International Conference on Automation and Computing
Abbreviated titleICAC 2016
CountryUnited Kingdom
CityColchester
Period7/09/168/09/16

Fingerprint

Camera Calibration
Cameras
Calibration
Camera
Error Detection
Error detection
Tracking System
Filter
Image denoising
Essential Component
Image Denoising
Enhancement
Strategy
Vision
Sensor
Three-dimensional
Sensors

Cite this

Alzarok, H., Fletcher, S., & Longstaff, A. P. (2016). A new strategy for improving vision based tracking accuracy based on utilization of camera calibration information. In 22nd International Conference on Automation and Computing: ICAC 2016: Tackling the New Challenges in Automation and Computing (pp. 278-283). [7604932] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IConAC.2016.7604932
Alzarok, Hamza ; Fletcher, Simon ; Longstaff, Andrew P. / A new strategy for improving vision based tracking accuracy based on utilization of camera calibration information. 22nd International Conference on Automation and Computing: ICAC 2016: Tackling the New Challenges in Automation and Computing. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 278-283
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abstract = "Camera calibration is one of the essential components of a vision based tracking system where the objective is to extract three dimensional information from a set of two dimensional frames. The information extracted from the calibration process is significant for examining the accuracy of the vision sensor, and thus further for estimating its effectiveness as a tracking system in real applications. This paper introduces another use for this information in which the proper location of the camera can be predicted. Anew mathematical formula based on utilizing the extracted calibration information was used for finding the optimum location for the camera, which provides the best detection accuracy. Moreover, the calibration information was also used for selecting the proper image Denoising filter. The results obtained proved the validity of the proposed formula in finding the desired camera location where the smallest detection errors can be produced. Also, results showed that the proper selection of the filter parameters led to a considerable enhancement in the overall accuracy of the camera, reducing the overall detection error by 0.2 mm.",
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Alzarok, H, Fletcher, S & Longstaff, AP 2016, A new strategy for improving vision based tracking accuracy based on utilization of camera calibration information. in 22nd International Conference on Automation and Computing: ICAC 2016: Tackling the New Challenges in Automation and Computing., 7604932, Institute of Electrical and Electronics Engineers Inc., pp. 278-283, 22nd International Conference on Automation and Computing, Colchester, United Kingdom, 7/09/16. https://doi.org/10.1109/IConAC.2016.7604932

A new strategy for improving vision based tracking accuracy based on utilization of camera calibration information. / Alzarok, Hamza; Fletcher, Simon; Longstaff, Andrew P.

22nd International Conference on Automation and Computing: ICAC 2016: Tackling the New Challenges in Automation and Computing. Institute of Electrical and Electronics Engineers Inc., 2016. p. 278-283 7604932.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Alzarok H, Fletcher S, Longstaff AP. A new strategy for improving vision based tracking accuracy based on utilization of camera calibration information. In 22nd International Conference on Automation and Computing: ICAC 2016: Tackling the New Challenges in Automation and Computing. Institute of Electrical and Electronics Engineers Inc. 2016. p. 278-283. 7604932 https://doi.org/10.1109/IConAC.2016.7604932