Počet záznamů: 1
Semisupervised Segmentation of UHD Video
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SYSNO ASEP 0494104 Druh ASEP C - Konferenční příspěvek (mezinárodní konf.) Zařazení RIV D - Článek ve sborníku Název Semisupervised Segmentation of UHD Video Tvůrce(i) Keruľ-Kmec, O. (CZ)
Pulc, Petr (UIVT-O) SAI, ORCID
Holeňa, Martin (UIVT-O) SAI, RIDZdroj.dok. ITAT 2018: Information Technologies – Applications and Theory. Proceedings of the 18th conference ITAT 2018. - Aachen : Technical University & CreateSpace Independent Publishing Platform, 2018 / Krajči S. - ISSN 1613-0073 Rozsah stran s. 100-107 Poč.str. 8 s. Forma vydání Online - E Akce ITAT 2018. Conference on Information Technologies – Applications and Theory /18./ Datum konání 21.09.2018 - 25.09.2018 Místo konání Plejsy Země SK - Slovensko Typ akce EUR Jazyk dok. eng - angličtina Země vyd. DE - Německo Klíč. slova UHD video ; Scene segmentation ; Keypoint detector ; Semisupervised classification ; Cluster regularization ; C-means Vědní obor RIV IN - Informatika Obor OECD Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) CEP GA18-18080S GA ČR - Grantová agentura ČR Institucionální podpora UIVT-O - RVO:67985807 EID SCOPUS 85053824287 Anotace One of the key preprocessing tasks in information 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 investigation 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 classification is combined with a frequently used keypoint detector 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 classifiers with different delays between the human-labelled video frame and classifier training. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2019 Elektronická adresa http://ceur-ws.org/Vol-2203/100.pdf
Počet záznamů: 1