Video retrieval based on patterns of oriented edge magnitude

K. Raghurama Holla; B. H. Shekar

doi:10.1145/2983402.2983433

Video retrieval based on patterns of oriented edge magnitude

K. Raghurama Holla
, B. H. Shekar

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

Abstract

In this work, a video retrieval system is proposed based on POEM (Patterns of Oriented Edge Magnitudes) descriptor. In the first stage, the input video is partitioned into shots based on Gabor moments and keyframes are selected from each shot based on Temporally Maximum Occurrence Frame (TMOF). In the next stage, the POEM descriptor is computed from each keyframe for robust image/frame representation. Given a query frame, the descriptor is obtained from it in a similar manner, and this descriptor is compared with the descriptors of the video keyframes using nearest neighbour matching technique to find the matching keyframe. We have conducted experiments on the TRECVID video segments to exhibit the superiority of the proposed approach for video retrieval applications.

Original language	English
Title of host publication	Proceedings of the 3rd International Symposium on Computer Vision and the Internet, VisionNet 2016
Publisher	Association for Computing Machinery
Pages	115-120
Number of pages	6
ISBN (Electronic)	9781450343015
DOIs	https://doi.org/10.1145/2983402.2983433
Publication status	Published - 21-09-2016
Event	3rd International Symposium on Computer Vision and the Internet, VisionNet 2016 - Jaipur, India Duration: 21-09-2016 → 24-09-2016

Publication series

Name	ACM International Conference Proceeding Series
Volume	21-24-September-2016

Conference

Conference	3rd International Symposium on Computer Vision and the Internet, VisionNet 2016
Country/Territory	India
City	Jaipur
Period	21-09-16 → 24-09-16

All Science Journal Classification (ASJC) codes

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

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10.1145/2983402.2983433

Cite this

Raghurama Holla, K., & Shekar, B. H. (2016). Video retrieval based on patterns of oriented edge magnitude. In Proceedings of the 3rd International Symposium on Computer Vision and the Internet, VisionNet 2016 (pp. 115-120). Article 2983433 (ACM International Conference Proceeding Series; Vol. 21-24-September-2016). Association for Computing Machinery. https://doi.org/10.1145/2983402.2983433

@inproceedings{08908ee8d14f4059915cfd560d871fef,

title = "Video retrieval based on patterns of oriented edge magnitude",

abstract = "In this work, a video retrieval system is proposed based on POEM (Patterns of Oriented Edge Magnitudes) descriptor. In the first stage, the input video is partitioned into shots based on Gabor moments and keyframes are selected from each shot based on Temporally Maximum Occurrence Frame (TMOF). In the next stage, the POEM descriptor is computed from each keyframe for robust image/frame representation. Given a query frame, the descriptor is obtained from it in a similar manner, and this descriptor is compared with the descriptors of the video keyframes using nearest neighbour matching technique to find the matching keyframe. We have conducted experiments on the TRECVID video segments to exhibit the superiority of the proposed approach for video retrieval applications.",

author = "\{Raghurama Holla\}, K. and Shekar, \{B. H.\}",

note = "Publisher Copyright: {\textcopyright} 2016 ACM.; 3rd International Symposium on Computer Vision and the Internet, VisionNet 2016 ; Conference date: 21-09-2016 Through 24-09-2016",

year = "2016",

month = sep,

day = "21",

doi = "10.1145/2983402.2983433",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

pages = "115--120",

booktitle = "Proceedings of the 3rd International Symposium on Computer Vision and the Internet, VisionNet 2016",

}

Raghurama Holla, K & Shekar, BH 2016, Video retrieval based on patterns of oriented edge magnitude. in Proceedings of the 3rd International Symposium on Computer Vision and the Internet, VisionNet 2016., 2983433, ACM International Conference Proceeding Series, vol. 21-24-September-2016, Association for Computing Machinery, pp. 115-120, 3rd International Symposium on Computer Vision and the Internet, VisionNet 2016, Jaipur, India, 21-09-16. https://doi.org/10.1145/2983402.2983433

Video retrieval based on patterns of oriented edge magnitude. / Raghurama Holla, K.; Shekar, B. H.
Proceedings of the 3rd International Symposium on Computer Vision and the Internet, VisionNet 2016. Association for Computing Machinery, 2016. p. 115-120 2983433 (ACM International Conference Proceeding Series; Vol. 21-24-September-2016).

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

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T1 - Video retrieval based on patterns of oriented edge magnitude

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AU - Shekar, B. H.

PY - 2016/9/21

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N2 - In this work, a video retrieval system is proposed based on POEM (Patterns of Oriented Edge Magnitudes) descriptor. In the first stage, the input video is partitioned into shots based on Gabor moments and keyframes are selected from each shot based on Temporally Maximum Occurrence Frame (TMOF). In the next stage, the POEM descriptor is computed from each keyframe for robust image/frame representation. Given a query frame, the descriptor is obtained from it in a similar manner, and this descriptor is compared with the descriptors of the video keyframes using nearest neighbour matching technique to find the matching keyframe. We have conducted experiments on the TRECVID video segments to exhibit the superiority of the proposed approach for video retrieval applications.

AB - In this work, a video retrieval system is proposed based on POEM (Patterns of Oriented Edge Magnitudes) descriptor. In the first stage, the input video is partitioned into shots based on Gabor moments and keyframes are selected from each shot based on Temporally Maximum Occurrence Frame (TMOF). In the next stage, the POEM descriptor is computed from each keyframe for robust image/frame representation. Given a query frame, the descriptor is obtained from it in a similar manner, and this descriptor is compared with the descriptors of the video keyframes using nearest neighbour matching technique to find the matching keyframe. We have conducted experiments on the TRECVID video segments to exhibit the superiority of the proposed approach for video retrieval applications.

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ER -

Video retrieval based on patterns of oriented edge magnitude

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All Science Journal Classification (ASJC) codes

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