Title: | Video summarization based on local features |
Authors: | Massaoudi, Mohammed Bahroun, Sahbi Zagrouba, Ezzeddine |
Citation: | WSCG 2017: poster papers proceedings: 25th International Conference in Central Europe on Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 13-17. |
Issue Date: | 2017 |
Publisher: | Václav Skala - UNION Agency |
Document type: | konferenční příspěvek conferenceObject |
URI: | wscg.zcu.cz/WSCG2017/!!_CSRN-2703.pdf http://hdl.handle.net/11025/29606 |
ISBN: | 978-80-86943-46-6 |
ISSN: | 2464-4617 |
Keywords: | shrnutí videa;extrakce klíčových snímků;zájmové body;SURF;FLANN |
Keywords in different language: | video summarization;keyframe extraction;interest points;SURF;FLANN |
Abstract: | Keyframe extraction process consists on presenting an abstract of the entire video with the most representative frames. It is one of the basic procedures relating to video retrieval and summary. This paper present a novel method for keyframe extraction based on SURF local features. First, we select a group of candidate frames from a video shot using a leap extraction technique. Then, SURF is used to detect and describe local features on the candidate frames. After that, we analyzed those features to eliminate near duplicate keyframes, helping to keep a compact set, using FLANN method. We developed a comparative study to evaluate our method with three state of the art approaches based on local features. The results show that our method overcomes those approaches. |
Rights: | © Václav Skala - Union Agency |
Appears in Collections: | WSCG 2017: Poster Papers Proceedings |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Massaoudi.pdf | Plný text | 1,24 MB | Adobe PDF | View/Open |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/29606
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