Saliency detection in MPEG and HEVC video using intra-frame and inter-frame distances

This paper proposes a video saliency detection model for MPEG and HEVC coded videos. The model extracts features from MPEG macro blocks and HEVC coding units. The feature variables are based on syntax elements and statistics of prediction error. The suitability of the selected features is verified t...

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Main Author: Shanableh, Tamer (author)
Format: article
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/11073/8818
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author Shanableh, Tamer
author_facet Shanableh, Tamer
author_role author
dc.creator.none.fl_str_mv Shanableh, Tamer
dc.date.none.fl_str_mv 2016-04
2017-05-01T05:44:03Z
2017-05-01T05:44:03Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv Shanableh, T. (2016). Saliency detection in mPEG and hEVC video using intra-frame and inter-frame distances. Signal, Image and Video Processing, 10(4), 703-709. doi:10.1007/s11760-015-0798-9
1863-1711
http://hdl.handle.net/11073/8818
10.1007/s11760-015-0798-9
dc.language.none.fl_str_mv en_US
dc.publisher.none.fl_str_mv Springer
dc.relation.none.fl_str_mv http://dx.doi.org/10.1007/s11760-015-0798-9
dc.subject.none.fl_str_mv Saliency detection
Feature extraction
MPEG
HEVC
dc.title.none.fl_str_mv Saliency detection in MPEG and HEVC video using intra-frame and inter-frame distances
dc.type.none.fl_str_mv Postprint
Peer-Reviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description This paper proposes a video saliency detection model for MPEG and HEVC coded videos. The model extracts features from MPEG macro blocks and HEVC coding units. The feature variables are based on syntax elements and statistics of prediction error. The suitability of the selected features is verified through the use of stepwise regression. Three saliency maps are generated based on intra-frame distances, inter-frame distances and global distances. The proposed model is tested using the eye-1 dataset compiled by Laurent Itti lab in the University of Southern California. The accuracy of the model is quantified by comparing saliency values at human saccade locations against saliency values at random locations. The comparison is performed in terms of Kullback-Leibler distances and receiver-operator curves. The proposed solution is compared against existing work using similar experimental setup. Experimental results revealed that a Kullback-Leibler distance of 2.14 and area under the receiver-operator curve of 0.936 are achieved.
format article
id aus_cfad017e777302ba6db19b722ad93005
identifier_str_mv Shanableh, T. (2016). Saliency detection in mPEG and hEVC video using intra-frame and inter-frame distances. Signal, Image and Video Processing, 10(4), 703-709. doi:10.1007/s11760-015-0798-9
1863-1711
10.1007/s11760-015-0798-9
language_invalid_str_mv en_US
network_acronym_str aus
network_name_str aus
oai_identifier_str oai:repository.aus.edu:11073/8818
publishDate 2016
publisher.none.fl_str_mv Springer
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Saliency detection in MPEG and HEVC video using intra-frame and inter-frame distancesShanableh, TamerSaliency detectionFeature extractionMPEGHEVCThis paper proposes a video saliency detection model for MPEG and HEVC coded videos. The model extracts features from MPEG macro blocks and HEVC coding units. The feature variables are based on syntax elements and statistics of prediction error. The suitability of the selected features is verified through the use of stepwise regression. Three saliency maps are generated based on intra-frame distances, inter-frame distances and global distances. The proposed model is tested using the eye-1 dataset compiled by Laurent Itti lab in the University of Southern California. The accuracy of the model is quantified by comparing saliency values at human saccade locations against saliency values at random locations. The comparison is performed in terms of Kullback-Leibler distances and receiver-operator curves. The proposed solution is compared against existing work using similar experimental setup. Experimental results revealed that a Kullback-Leibler distance of 2.14 and area under the receiver-operator curve of 0.936 are achieved.Springer2017-05-01T05:44:03Z2017-05-01T05:44:03Z2016-04PostprintPeer-Reviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfShanableh, T. (2016). Saliency detection in mPEG and hEVC video using intra-frame and inter-frame distances. Signal, Image and Video Processing, 10(4), 703-709. doi:10.1007/s11760-015-0798-91863-1711http://hdl.handle.net/11073/881810.1007/s11760-015-0798-9en_UShttp://dx.doi.org/10.1007/s11760-015-0798-9oai:repository.aus.edu:11073/88182024-08-22T12:07:25Z
spellingShingle Saliency detection in MPEG and HEVC video using intra-frame and inter-frame distances
Shanableh, Tamer
Saliency detection
Feature extraction
MPEG
HEVC
status_str publishedVersion
title Saliency detection in MPEG and HEVC video using intra-frame and inter-frame distances
title_full Saliency detection in MPEG and HEVC video using intra-frame and inter-frame distances
title_fullStr Saliency detection in MPEG and HEVC video using intra-frame and inter-frame distances
title_full_unstemmed Saliency detection in MPEG and HEVC video using intra-frame and inter-frame distances
title_short Saliency detection in MPEG and HEVC video using intra-frame and inter-frame distances
title_sort Saliency detection in MPEG and HEVC video using intra-frame and inter-frame distances
topic Saliency detection
Feature extraction
MPEG
HEVC
url http://hdl.handle.net/11073/8818