SEDMIDUBSKÝ, Jan, Michal BATKO and Pavel ZEZULA. Face-based People Searching in Videos. In P. Serdyukov et al. 35th European Conference on Information Retrieval (ECIR 2013), LNCS 7814. Berlin Heidelberg: Springer-Verlag. p. 853-856. ISBN 978-3-642-36972-8. doi:10.1007/978-3-642-36973-5_101. 2013.
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Basic information
Original name Face-based People Searching in Videos
Authors SEDMIDUBSKÝ, Jan (203 Czech Republic, guarantor, belonging to the institution), Michal BATKO (203 Czech Republic, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
Edition Berlin Heidelberg, 35th European Conference on Information Retrieval (ECIR 2013), LNCS 7814, p. 853-856, 4 pp. 2013.
Publisher Springer-Verlag
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Russian Federation
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/13:00065975
Organization unit Faculty of Informatics
ISBN 978-3-642-36972-8
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-642-36973-5_101
Keywords in English face recognition; video retrieval; similarity search; MPEG-7
Tags DISA
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 24/4/2014 21:46.
Abstract
We propose a system for retrieving people according to their faces in unannotated video streams. The system processes input videos to extract key-frames on which faces are detected. The detected faces are automatically grouped together to create clusters containing snapshots of the same person. The system also facilitates annotation and manual manipulations with created clusters. On the processed videos the system offers to search for persons in three distinct operations applicable to various scenarios. The system is presented online by indexing five high-quality video streams with the total length of nearly five hours.
Links
GBP103/12/G084, research and development projectName: Centrum pro multi-modální interpretaci dat velkého rozsahu
Investor: Czech Science Foundation
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