Publication Details

Brno University of Technology at TRECVid 2008

CHMELAŘ Petr, BERAN Vítězslav, HEROUT Adam, HRADIŠ Michal, JURÁNEK Roman, LÁNÍK Aleš, MLÍCH Jozef, NAVRÁTIL Jan, ŘEZNÍČEK Ivo, ŽÁK Pavel and ZEMČÍK Pavel. Brno University of Technology at TRECVid 2008. In: Proceedings of TRECVID 2008. Gaithersburg: National Institute of Standards and Technology, 2008, pp. 1-16.
Czech title
Brno University of Technology at TRECVid 2008
Type
conference paper
Language
english
Authors
Chmelař Petr, Ing. (DIFS FIT BUT)
Beran Vítězslav, doc. Ing., Ph.D. (DCGM FIT BUT)
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT)
Hradiš Michal, Ing., Ph.D. (DCGM FIT BUT)
Juránek Roman, Ing., Ph.D. (DCGM FIT BUT)
Láník Aleš, Ing. (DCGM FIT BUT)
Mlích Jozef, Ing. (DCGM FIT BUT)
Navrátil Jan, Ing., Ph.D. (DCGM FIT BUT)
Řezníček Ivo, Ing. (DCGM FIT BUT)
Žák Pavel, Ing. (DCGM FIT BUT)
Zemčík Pavel, prof. Dr. Ing. (DCGM FIT BUT)
URL
Keywords
TRECVid 2008, Brno, Surveillance event detection pilot, Content-based copy detection pilot, High-level feature extraction, Video Search.
Abstract

In this paper we describe our experiments in all task of TRECVid 2008. This year, we have concentrated
mainly on the local (affine covariant) image features and its transformation into a search-able form for the
Content-based copy detection pilot together with the indexing and search techniques for the Search task and a
practical test of the background subtraction and trajectory generation algorithms for the Surveillance pilot.
In brief, we have submitted the following tasks:
    1. Surveillance event detection pilot. We have participated in the detection of the following events
         - PersonRuns, ObjectPut, ElevatorNoEntry and OpposingFlow. It has been based mainly on
         advanced masking and background subtractions and extracted trajectories.
    2. Content-based copy detection pilot. We have submitted one run based on search of the joint
         image features - global (color, texture) and local features (SIFT).
    3. High-level feature extraction. We have used two training methods based on SVM using color,
         texture and face image features. First only selected subset of the training data, second all the
         annotated data were used for the training.
    4. Search. We have performed two fully automatic IR experiments based on the text of the queries
         and ASR/MT provided by NIST and the data consumed by the High-level feature extraction task.
    5. Rushes summarization, to which is dedicated a separate paper [2].

Published
2008
Pages
1-16
Proceedings
Proceedings of TRECVID 2008
Conference
2008 TRECVID Workshop, NIST, Gaithersburg, MD, US
Publisher
National Institute of Standards and Technology
Place
Gaithersburg, US
BibTeX 
@INPROCEEDINGS{FITPUB8828,
   author = "Petr Chmela\v{r} and V\'{i}t\v{e}zslav Beran and Adam Herout and Michal Hradi\v{s} and Roman Jur\'{a}nek and Ale\v{s} L\'{a}n\'{i}k and Jozef Ml\'{i}ch and Jan Navr\'{a}til and Ivo \v{R}ezn\'{i}\v{c}ek and Pavel \v{Z}\'{a}k and Pavel Zem\v{c}\'{i}k",
   title = "Brno University of Technology at TRECVid 2008",
   pages = "1--16",
   booktitle = "Proceedings of TRECVID 2008",
   year = 2008,
   location = "Gaithersburg, US",
   publisher = "National Institute of Standards and Technology",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/8828"
}
Back to top