@InProceedings{CámaraChávezCorPrePhiAlb:2006:ViSeSu,
author = "C{\'a}mara Ch{\'a}vez, Guillermo and Cord, Matthieu and
Precioso, Frederic and Philipp-Foliguet, Sylvie and de Albuquerque
Ara{\'u}jo, Arnaldo",
affiliation = "{Equipe Traiment des Images et du Signal - ENSEA} and {Equipe
Traiment des Images et du Signal - ENSEA} and {Equipe Traiment des
Images et du Signal - ENSEA} and {Equipe Traiment des Images et du
Signal - ENSEA} and {Departamento de Ci{\^e}ncia da
Computa{\c{c}}{\~a}o - UFMG}",
title = "Video Segmentation by Supervised Learning",
booktitle = "Proceedings...",
year = "2006",
editor = "Oliveira Neto, Manuel Menezes de and Carceroni, Rodrigo Lima",
organization = "Brazilian Symposium on Computer Graphics and Image Processing, 19.
(SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "video segmentation, cut detection, supervised learning.",
abstract = "In most of video shot boundary detection algorithms, proposed in
the literature, several parameters and thresholds have to be set
in order to achieve good results. In this paper, to get rid of
parameters and thresholds, we explore a supervised classification
method for video shot segmentation. We transform the temporal
segmentation into a class categorization issue. Our approach
defines a uniform framework for combining different kinds of
features extracted from the video. Our method does not require any
pre-processing step to compensate motion or post-processing
filtering to eliminate false detected transitions. The
experiments, following strictly the TRECVID 2002 competition
protocol, provide very good results dealing with a large amount of
features thanks to our kernel-based SVM classification method.",
conference-location = "Manaus, AM, Brazil",
conference-year = "8-11 Oct. 2006",
doi = "10.1109/SIBGRAPI.2006.48",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2006.48",
language = "en",
ibi = "6qtX3pFwXQZG2LgkFdY/LPfUC",
url = "http://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/LPfUC",
targetfile = "sibgrapi_camara_video.pdf",
urlaccessdate = "2025, Feb. 10"
}