Local smoothness for global optical flow

Lars Lau Rakêt

doi:10.1109/ICIP.2012.6674231

Local smoothness for global optical flow

Lars Lau Rakêt

Datalogisk Institut

Abstract

We consider the problem of estimating the “smoothness parameter” that controls the tradeoff between data fidelity and regularity in optical flow estimation. We start by reviewing the problem of global estimation using the Optimal Prediction Principle (OPP) by Zimmer et al. Inspired by this technique and work on local-global optical flow we propose a simple method for fusing optical flow estimates of different smoothness by evaluating interpolation quality locally by means of L1 block match on the corresponding set of gradient images. We illustrate the method in a setting where optical flows are estimated by a TV-L1 energy. On average this procedure reduces the average endpoint error by 15% over flows estimated using the OPP, and gives flow fields that are consistently better than the single best flows with a fixed smoothness parameter.

Originalsprog	Engelsk
Titel	2012 19th IEEE International Conference on Image Processing (ICIP)
Antal sider	4
Forlag	IEEE
Publikationsdato	2012
ISBN (Trykt)	978-1-4673-2534-9
ISBN (Elektronisk)	978-1-4673-2533-2
DOI	https://doi.org/10.1109/ICIP.2012.6674231
Status	Udgivet - 2012
Begivenhed	2012 19th IEEE International Conference on Image Processing - Orlando , USA Varighed: 30 sep. 2012 → 3 okt. 2012 Konferencens nummer: 19

Konference

Konference	2012 19th IEEE International Conference on Image Processing
Nummer	19
Land/Område	USA
By	Orlando
Periode	30/09/2012 → 03/10/2012

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10.1109/ICIP.2012.6674231

Citationsformater

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title = "Local smoothness for global optical flow",

abstract = "We consider the problem of estimating the “smoothness parameter” that controls the tradeoff between data fidelity and regularity in optical flow estimation. We start by reviewing the problem of global estimation using the Optimal Prediction Principle (OPP) by Zimmer et al. Inspired by this technique and work on local-global optical flow we propose a simple method for fusing optical flow estimates of different smoothness by evaluating interpolation quality locally by means of L1 block match on the corresponding set of gradient images. We illustrate the method in a setting where optical flows are estimated by a TV-L1 energy. On average this procedure reduces the average endpoint error by 15% over flows estimated using the OPP, and gives flow fields that are consistently better than the single best flows with a fixed smoothness parameter.",

author = "Rak{\^e}t, {Lars Lau}",

year = "2012",

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language = "English",

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N1 - Conference code: 19

PY - 2012

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N2 - We consider the problem of estimating the “smoothness parameter” that controls the tradeoff between data fidelity and regularity in optical flow estimation. We start by reviewing the problem of global estimation using the Optimal Prediction Principle (OPP) by Zimmer et al. Inspired by this technique and work on local-global optical flow we propose a simple method for fusing optical flow estimates of different smoothness by evaluating interpolation quality locally by means of L1 block match on the corresponding set of gradient images. We illustrate the method in a setting where optical flows are estimated by a TV-L1 energy. On average this procedure reduces the average endpoint error by 15% over flows estimated using the OPP, and gives flow fields that are consistently better than the single best flows with a fixed smoothness parameter.

AB - We consider the problem of estimating the “smoothness parameter” that controls the tradeoff between data fidelity and regularity in optical flow estimation. We start by reviewing the problem of global estimation using the Optimal Prediction Principle (OPP) by Zimmer et al. Inspired by this technique and work on local-global optical flow we propose a simple method for fusing optical flow estimates of different smoothness by evaluating interpolation quality locally by means of L1 block match on the corresponding set of gradient images. We illustrate the method in a setting where optical flows are estimated by a TV-L1 energy. On average this procedure reduces the average endpoint error by 15% over flows estimated using the OPP, and gives flow fields that are consistently better than the single best flows with a fixed smoothness parameter.

U2 - 10.1109/ICIP.2012.6674231

DO - 10.1109/ICIP.2012.6674231

M3 - Article in proceedings

SN - 978-1-4673-2534-9

BT - 2012 19th IEEE International Conference on Image Processing (ICIP)

PB - IEEE

T2 - 2012 19th IEEE International Conference on Image Processing

Y2 - 30 September 2012 through 3 October 2012

ER -

Local smoothness for global optical flow

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