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Statements

Subject Item
n2:RIV%2F00216305%3A26230%2F13%3APU106367%21RIV14-MV0-26230___
rdf:type
skos:Concept n21:Vysledek
dcterms:description
This paper presents an approach for detection of differences between two visually identical video sequences. The video processing task for detection of short- and long-term changes between two video sequences is defined in detail. The algorithm comparing two video sequences (reference and query) is introduced together with definition of particular situations that the algorithm must be able to detect: re-written parts, removals or injected parts. The image processing methods are selected to be robust to several practical distortions that might appear in defined task. The appropriate computer-vision methods are presented and discussed, then proposed method and experiments are introduced and evaluated on manually generated dataset. Main focus of this work is on comparison of two different approaches for keyframe extraction: The first, more robust one is based on local features tracking, which we attempt to replace with computationally much less-expensive global descriptor approach with preser This paper presents an approach for detection of differences between two visually identical video sequences. The video processing task for detection of short- and long-term changes between two video sequences is defined in detail. The algorithm comparing two video sequences (reference and query) is introduced together with definition of particular situations that the algorithm must be able to detect: re-written parts, removals or injected parts. The image processing methods are selected to be robust to several practical distortions that might appear in defined task. The appropriate computer-vision methods are presented and discussed, then proposed method and experiments are introduced and evaluated on manually generated dataset. Main focus of this work is on comparison of two different approaches for keyframe extraction: The first, more robust one is based on local features tracking, which we attempt to replace with computationally much less-expensive global descriptor approach with preser
dcterms:title
Dissimilarity Detection of Two Video Sequences Dissimilarity Detection of Two Video Sequences
skos:prefLabel
Dissimilarity Detection of Two Video Sequences Dissimilarity Detection of Two Video Sequences
skos:notation
RIV/00216305:26230/13:PU106367!RIV14-MV0-26230___
n21:predkladatel
n22:orjk%3A26230
n4:aktivita
n7:P
n4:aktivity
P(7H12006), P(VG20102015006)
n4:dodaniDat
n8:2014
n4:domaciTvurceVysledku
n20:1542826 n20:9340386 n20:6220703
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n17:D
n4:duvernostUdaju
n13:S
n4:entitaPredkladatele
n19:predkladatel
n4:idSjednocenehoVysledku
69927
n4:idVysledku
RIV/00216305:26230/13:PU106367
n4:jazykVysledku
n16:eng
n4:klicovaSlova
Video comparison, Dissimilarity, Histogram, Motion segmentation, Similarity matrix, Temporal analysis, Keyframe detection, Video segmentation
n4:klicoveSlovo
n5:Temporal%20analysis n5:Similarity%20matrix n5:Keyframe%20detection n5:Video%20comparison n5:Video%20segmentation n5:Motion%20segmentation n5:Histogram n5:Dissimilarity
n4:kontrolniKodProRIV
[EE8B41361E34]
n4:mistoKonaniAkce
Smolenice
n4:mistoVydani
Smolenice
n4:nazevZdroje
Proceedings of SCCG 2013
n4:obor
n14:IN
n4:pocetDomacichTvurcuVysledku
3
n4:pocetTvurcuVysledku
3
n4:projekt
n11:7H12006 n11:VG20102015006
n4:rokUplatneniVysledku
n8:2013
n4:tvurceVysledku
Zemčík, Pavel Beran, Vítězslav Klicnar, Lukáš
n4:typAkce
n18:EUR
n4:zahajeniAkce
2013-05-01+02:00
s:numberOfPages
4
n9:hasPublisher
Univerzita Komenského v Bratislave
n10:isbn
978-80-223-3377-1
n12:organizacniJednotka
26230