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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

  • DOI - Digital Object Identifier

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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • 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

  • 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