Improving the Accuracy of Intelligent Pose Estimation Systems Through Low Level Image Processing Operations

Jannik Christian Lærkegård Pedersen, Mattias Foltmar Sander, Niklas Fruerlund Jensen, Jonas Lasham Lakhrissi, Mikkel Gede Hansen, Patrick Staalbo, Andreas Wulff-Abramsson

Research output: Contribution to journalConference article in JournalResearchpeer-review

Abstract

The development of powerful and popular machine learning driven pose estimation systems have been on the rise during the past years. In this research we have investigated how the accuracy level can be increased by applying low level image processing techniques unto the footage before they are submitted to the pose estimation system. The techniques used were high and low contrast, histogram equalization, sharpness and canny edge detection. By applying them on datasets, containing different environments and lighting conditions the system’s accuracy was increased, ranging from 0.29% increase to 38.37% increase dependent on the context. These increases have potential to upgrade the pose estimation system to be less lighting sensitive.
Original languageDanish
Journalforeløbig ukendt
Pages (from-to)1
Number of pages4
Publication statusPublished - 4 May 2019
EventInternational Conference on Digital Image & Signal Processing (DISP’19) - Oxford, United Kingdom
Duration: 29 Apr 201930 Apr 2019

Conference

ConferenceInternational Conference on Digital Image & Signal Processing (DISP’19)
CountryUnited Kingdom
CityOxford
Period29/04/201930/04/2019

Cite this

Lærkegård Pedersen, J. C., Foltmar Sander, M., Fruerlund Jensen, N., Lasham Lakhrissi, J., Hansen, M. G., Staalbo, P., & Wulff-Abramsson, A. (2019). Improving the Accuracy of Intelligent Pose Estimation Systems Through Low Level Image Processing Operations. foreløbig ukendt, 1.
Lærkegård Pedersen, Jannik Christian ; Foltmar Sander, Mattias ; Fruerlund Jensen, Niklas ; Lasham Lakhrissi, Jonas ; Hansen, Mikkel Gede ; Staalbo, Patrick ; Wulff-Abramsson, Andreas. / Improving the Accuracy of Intelligent Pose Estimation Systems Through Low Level Image Processing Operations. In: foreløbig ukendt. 2019 ; pp. 1.
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title = "Improving the Accuracy of Intelligent Pose Estimation Systems Through Low Level Image Processing Operations",
abstract = "The development of powerful and popular machine learning driven pose estimation systems have been on the rise during the past years. In this research we have investigated how the accuracy level can be increased by applying low level image processing techniques unto the footage before they are submitted to the pose estimation system. The techniques used were high and low contrast, histogram equalization, sharpness and canny edge detection. By applying them on datasets, containing different environments and lighting conditions the system’s accuracy was increased, ranging from 0.29{\%} increase to 38.37{\%} increase dependent on the context. These increases have potential to upgrade the pose estimation system to be less lighting sensitive.",
keywords = "OpenPose, Image processing, Limb Estimation, Histogram equalization, Low-.level operations, Image Contrast, Sharpness, Canny edge detection",
author = "{L{\ae}rkeg{\aa}rd Pedersen}, {Jannik Christian} and {Foltmar Sander}, Mattias and {Fruerlund Jensen}, Niklas and {Lasham Lakhrissi}, Jonas and Hansen, {Mikkel Gede} and Patrick Staalbo and Andreas Wulff-Abramsson",
year = "2019",
month = "5",
day = "4",
language = "Dansk",
pages = "1",
journal = "forel{\o}big ukendt",

}

Lærkegård Pedersen, JC, Foltmar Sander, M, Fruerlund Jensen, N, Lasham Lakhrissi, J, Hansen, MG, Staalbo, P & Wulff-Abramsson, A 2019, 'Improving the Accuracy of Intelligent Pose Estimation Systems Through Low Level Image Processing Operations', foreløbig ukendt, pp. 1.

Improving the Accuracy of Intelligent Pose Estimation Systems Through Low Level Image Processing Operations. / Lærkegård Pedersen, Jannik Christian; Foltmar Sander, Mattias ; Fruerlund Jensen, Niklas ; Lasham Lakhrissi, Jonas ; Hansen, Mikkel Gede; Staalbo, Patrick ; Wulff-Abramsson, Andreas.

In: foreløbig ukendt, 04.05.2019, p. 1.

Research output: Contribution to journalConference article in JournalResearchpeer-review

TY - GEN

T1 - Improving the Accuracy of Intelligent Pose Estimation Systems Through Low Level Image Processing Operations

AU - Lærkegård Pedersen, Jannik Christian

AU - Foltmar Sander, Mattias

AU - Fruerlund Jensen, Niklas

AU - Lasham Lakhrissi, Jonas

AU - Hansen, Mikkel Gede

AU - Staalbo, Patrick

AU - Wulff-Abramsson, Andreas

PY - 2019/5/4

Y1 - 2019/5/4

N2 - The development of powerful and popular machine learning driven pose estimation systems have been on the rise during the past years. In this research we have investigated how the accuracy level can be increased by applying low level image processing techniques unto the footage before they are submitted to the pose estimation system. The techniques used were high and low contrast, histogram equalization, sharpness and canny edge detection. By applying them on datasets, containing different environments and lighting conditions the system’s accuracy was increased, ranging from 0.29% increase to 38.37% increase dependent on the context. These increases have potential to upgrade the pose estimation system to be less lighting sensitive.

AB - The development of powerful and popular machine learning driven pose estimation systems have been on the rise during the past years. In this research we have investigated how the accuracy level can be increased by applying low level image processing techniques unto the footage before they are submitted to the pose estimation system. The techniques used were high and low contrast, histogram equalization, sharpness and canny edge detection. By applying them on datasets, containing different environments and lighting conditions the system’s accuracy was increased, ranging from 0.29% increase to 38.37% increase dependent on the context. These increases have potential to upgrade the pose estimation system to be less lighting sensitive.

KW - OpenPose

KW - Image processing

KW - Limb Estimation

KW - Histogram equalization

KW - Low-.level operations

KW - Image Contrast

KW - Sharpness

KW - Canny edge detection

M3 - Konferenceartikel i tidsskrift

SP - 1

JO - foreløbig ukendt

JF - foreløbig ukendt

ER -

Lærkegård Pedersen JC, Foltmar Sander M, Fruerlund Jensen N, Lasham Lakhrissi J, Hansen MG, Staalbo P et al. Improving the Accuracy of Intelligent Pose Estimation Systems Through Low Level Image Processing Operations. foreløbig ukendt. 2019 May 4;1.