Visual quality assessment of reconstructed background images

Aditee Shrotre; Lina Karam

doi:10.1109/QoMEX.2016.7498954

Visual quality assessment of reconstructed background images

Aditee Shrotre, Lina Karam

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

A clean background image is of great importance in multiple applications such as video surveillance, object tracking and context-based video encoding, but acquiring a clean background image in public areas is seldom possible. Many algorithms have been developed to initialize the background from videos and images. This paper presents a database consisting of 13 different scenes that can be used for benchmarking the performance of background initialization algorithms. We also conducted a subjective study on the perceptual quality of background images that are reconstructed using existing background initialization algorithms. The obtained subjective scores are used to evaluate existing image quality metrics and their capability in predicting the perceived quality of reconstructed background images.

Original language	English (US)
Title of host publication	2016 8th International Conference on Quality of Multimedia Experience, QoMEX 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509003549
DOIs	https://doi.org/10.1109/QoMEX.2016.7498954
State	Published - Jun 23 2016
Event	8th International Conference on Quality of Multimedia Experience, QoMEX 2016 - Lisbon, Portugal Duration: Jun 6 2016 → Jun 8 2016

Other

Other	8th International Conference on Quality of Multimedia Experience, QoMEX 2016
Country/Territory	Portugal
City	Lisbon
Period	6/6/16 → 6/8/16

Keywords

Background Reconstruction
Image Database
Image Quality Assessment
Perceptual Quality
Subjective Evaluation

ASJC Scopus subject areas

Computer Networks and Communications
Media Technology
Communication

Access to Document

10.1109/QoMEX.2016.7498954

Cite this

Shrotre, A & Karam, L 2016, Visual quality assessment of reconstructed background images. in 2016 8th International Conference on Quality of Multimedia Experience, QoMEX 2016., 7498954, Institute of Electrical and Electronics Engineers Inc., 8th International Conference on Quality of Multimedia Experience, QoMEX 2016, Lisbon, Portugal, 6/6/16. https://doi.org/10.1109/QoMEX.2016.7498954

@inproceedings{639bb5d5fc824b9dbecb5070f91da7ac,

title = "Visual quality assessment of reconstructed background images",

abstract = "A clean background image is of great importance in multiple applications such as video surveillance, object tracking and context-based video encoding, but acquiring a clean background image in public areas is seldom possible. Many algorithms have been developed to initialize the background from videos and images. This paper presents a database consisting of 13 different scenes that can be used for benchmarking the performance of background initialization algorithms. We also conducted a subjective study on the perceptual quality of background images that are reconstructed using existing background initialization algorithms. The obtained subjective scores are used to evaluate existing image quality metrics and their capability in predicting the perceived quality of reconstructed background images.",

keywords = "Background Reconstruction, Image Database, Image Quality Assessment, Perceptual Quality, Subjective Evaluation",

author = "Aditee Shrotre and Lina Karam",

year = "2016",

month = jun,

day = "23",

doi = "10.1109/QoMEX.2016.7498954",

language = "English (US)",

booktitle = "2016 8th International Conference on Quality of Multimedia Experience, QoMEX 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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note = "8th International Conference on Quality of Multimedia Experience, QoMEX 2016 ; Conference date: 06-06-2016 Through 08-06-2016",

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AU - Karam, Lina

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N2 - A clean background image is of great importance in multiple applications such as video surveillance, object tracking and context-based video encoding, but acquiring a clean background image in public areas is seldom possible. Many algorithms have been developed to initialize the background from videos and images. This paper presents a database consisting of 13 different scenes that can be used for benchmarking the performance of background initialization algorithms. We also conducted a subjective study on the perceptual quality of background images that are reconstructed using existing background initialization algorithms. The obtained subjective scores are used to evaluate existing image quality metrics and their capability in predicting the perceived quality of reconstructed background images.

AB - A clean background image is of great importance in multiple applications such as video surveillance, object tracking and context-based video encoding, but acquiring a clean background image in public areas is seldom possible. Many algorithms have been developed to initialize the background from videos and images. This paper presents a database consisting of 13 different scenes that can be used for benchmarking the performance of background initialization algorithms. We also conducted a subjective study on the perceptual quality of background images that are reconstructed using existing background initialization algorithms. The obtained subjective scores are used to evaluate existing image quality metrics and their capability in predicting the perceived quality of reconstructed background images.

KW - Background Reconstruction

KW - Image Database

KW - Image Quality Assessment

KW - Perceptual Quality

KW - Subjective Evaluation

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DO - 10.1109/QoMEX.2016.7498954

M3 - Conference contribution

AN - SCOPUS:84979647955

BT - 2016 8th International Conference on Quality of Multimedia Experience, QoMEX 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 8th International Conference on Quality of Multimedia Experience, QoMEX 2016

Y2 - 6 June 2016 through 8 June 2016

ER -

Visual quality assessment of reconstructed background images

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Keywords

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