A compact parametric solution to depth sensor calibration

Andrew Spek; Tom Drummond

doi:10.5244/C.31.179

A compact parametric solution to depth sensor calibration

Andrew Spek, Tom Drummond

Electrical and Computer Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

Abstract

We present a method for calibration of low-cost depth sensors such as the Microsoft Kinect. We show this method is effective at correcting the structured sensor error using a compact parametric solution, that uses only a small fraction of the number of parameters used in many existing approaches. Additionally we provide this calibration as an open-source implementation, with limited required external dependencies. We demonstrate our approach can optimise directly for a geometric depth and radial distortion calibration function in minutes on modern hardware.

Original language	English
Title of host publication	British Machine Vision Conference Proceedings 2017
Editors	Krystian Mikolajczyk, Gabriel Brostow
Place of Publication	London UK
Publisher	British Machine Vision Association
Number of pages	12
ISBN (Electronic)	9781901725605
ISBN (Print)	190172560X
DOIs	https://doi.org/10.5244/C.31.179
Publication status	Published - 2017
Event	British Machine Vision Conference 2017 - Royal Geographic Society of London, London, United Kingdom Duration: 4 Sept 2017 → 7 Sept 2017 Conference number: 28th https://bmvc2017.london/ https://dblp.org/db/conf/bmvc/bmvc2017.html

Conference

Conference	British Machine Vision Conference 2017
Abbreviated title	BMVC 2017
Country/Territory	United Kingdom
City	London
Period	4/09/17 → 7/09/17
Internet address	https://bmvc2017.london/ https://dblp.org/db/conf/bmvc/bmvc2017.html

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10.5244/C.31.179

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Cite this

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title = "A compact parametric solution to depth sensor calibration",

abstract = "We present a method for calibration of low-cost depth sensors such as the Microsoft Kinect. We show this method is effective at correcting the structured sensor error using a compact parametric solution, that uses only a small fraction of the number of parameters used in many existing approaches. Additionally we provide this calibration as an open-source implementation, with limited required external dependencies. We demonstrate our approach can optimise directly for a geometric depth and radial distortion calibration function in minutes on modern hardware.",

author = "Andrew Spek and Tom Drummond",

year = "2017",

doi = "10.5244/C.31.179",

language = "English",

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editor = "Krystian Mikolajczyk and Gabriel Brostow",

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publisher = "British Machine Vision Association",

note = "British Machine Vision Conference 2017, BMVC 2017 ; Conference date: 04-09-2017 Through 07-09-2017",

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AB - We present a method for calibration of low-cost depth sensors such as the Microsoft Kinect. We show this method is effective at correcting the structured sensor error using a compact parametric solution, that uses only a small fraction of the number of parameters used in many existing approaches. Additionally we provide this calibration as an open-source implementation, with limited required external dependencies. We demonstrate our approach can optimise directly for a geometric depth and radial distortion calibration function in minutes on modern hardware.

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M3 - Conference Paper

SN - 190172560X

BT - British Machine Vision Conference Proceedings 2017

A2 - Mikolajczyk, Krystian

A2 - Brostow, Gabriel

PB - British Machine Vision Association

CY - London UK

T2 - British Machine Vision Conference 2017

Y2 - 4 September 2017 through 7 September 2017

ER -

A compact parametric solution to depth sensor calibration

Abstract

Conference

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