Full metadata record
DC pole | Hodnota | Jazyk |
---|---|---|
dc.contributor.author | Massaoudi, Mohammed | |
dc.contributor.author | Bahroun, Sahbi | |
dc.contributor.author | Zagrouba, Ezzeddine | |
dc.contributor.editor | Skala, Václav | |
dc.date.accessioned | 2018-04-16T08:28:57Z | - |
dc.date.available | 2018-04-16T08:28:57Z | - |
dc.date.issued | 2017 | |
dc.identifier.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. | en |
dc.identifier.isbn | 978-80-86943-46-6 | |
dc.identifier.issn | 2464-4617 | |
dc.identifier.uri | wscg.zcu.cz/WSCG2017/!!_CSRN-2703.pdf | |
dc.identifier.uri | http://hdl.handle.net/11025/29606 | |
dc.description.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. | en |
dc.format | 5 s. | cs |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | en |
dc.publisher | Václav Skala - UNION Agency | en |
dc.relation.ispartofseries | WSCG 2017: poster papers proceedings | en |
dc.rights | © Václav Skala - Union Agency | cs |
dc.subject | shrnutí videa | cs |
dc.subject | extrakce klíčových snímků | cs |
dc.subject | zájmové body | cs |
dc.subject | SURF | cs |
dc.subject | FLANN | cs |
dc.title | Video summarization based on local features | en |
dc.type | konferenční příspěvek | cs |
dc.type | conferenceObject | en |
dc.rights.access | openAccess | en |
dc.type.version | publishedVersion | en |
dc.subject.translated | video summarization | en |
dc.subject.translated | keyframe extraction | en |
dc.subject.translated | interest points | en |
dc.subject.translated | SURF | en |
dc.subject.translated | FLANN | en |
dc.type.status | Peer-reviewed | en |
Vyskytuje se v kolekcích: | WSCG 2017: Poster Papers Proceedings |
Soubory připojené k záznamu:
Soubor | Popis | Velikost | Formát | |
---|---|---|---|---|
Massaoudi.pdf | Plný text | 1,24 MB | Adobe PDF | Zobrazit/otevřít |
Použijte tento identifikátor k citaci nebo jako odkaz na tento záznam:
http://hdl.handle.net/11025/29606
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