Semisupervised segmentation of UHD video
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F18%3A00324673" target="_blank" >RIV/68407700:21240/18:00324673 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Semisupervised segmentation of UHD video
Original language description
One of the key preprocessing tasks in informa- tion retrieveal from video is the segmentation of the scene, primarily its segmentation into foreground objects and the background. This is actually a classification task, but with the specific property that it is very time consuming and costly to obtain human-labelled training data for classifier training. That suggests to use semisupervised classifiers to this end. The presented work in progress reports the inves- tigation of semisupervised classification methods based on cluster regularization and on fuzzy c-means in connection with the foreground / background segmentation task. To classify as many video frames as possible using only a single human-based frame, the semisupervised classifica- tion is combined with a frequently used keypoint detec- tor based on a combination of a corner detection method with a visual descriptor method. The paper experimentally compares both methods, and for the first of them, also clas- sifiers with different delays between the human-labelled video frame and classifier training.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA18-18080S" target="_blank" >GA18-18080S: Fusion-Based Knowledge Discovery in Human Activity Data</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 18th Conference Information Technologies - Applications and Theory (ITAT 2018)
ISBN
9781727267198
ISSN
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e-ISSN
1613-0073
Number of pages
8
Pages from-to
100-107
Publisher name
CEUR Workshop Proceedings
Place of publication
Aachen
Event location
Krompachy
Event date
Sep 21, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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