Identifying important people in broadcast news videos

Hua Gao; Hazim Kemal Ekenel; Rainer Stiefelhagen

Identifying important people in broadcast news videos

Hua Gao^*, Hazim Kemal Ekenel, Rainer Stiefelhagen

^*Corresponding author for this work

Karlsruhe Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Automatic face identification in multimedia archives such as broadcast news videos is useful for indexing or retrieving documents based on important persons that appear in the video. In this paper, we propose a system which automatically detects a list of important targets such as anchor speakers or active politicians in broadcast news videos. This involves several steps including detecting faces in various conditions, associating faces to tracks and identifying whether a face track contains certain faces defined in a watch list. We evaluated this system on a database, which contains about 36 hours of broadcast news videos. Experiments show that our system achieves a very high precision with a reasonable recall rate.

Original language	English
Title of host publication	Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011
Pages	414-417
Number of pages	4
Publication status	Published - 2011
Externally published	Yes
Event	12th IAPR Conference on Machine Vision Applications, MVA 2011 - Nara, Japan Duration: 13 Jun 2011 → 15 Jun 2011

Publication series

Name	Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

Conference

Conference	12th IAPR Conference on Machine Vision Applications, MVA 2011
Country/Territory	Japan
City	Nara
Period	13/06/11 → 15/06/11

Cite this

@inproceedings{9c17af91c2c542aa963116e2aa032c32,

title = "Identifying important people in broadcast news videos",

abstract = "Automatic face identification in multimedia archives such as broadcast news videos is useful for indexing or retrieving documents based on important persons that appear in the video. In this paper, we propose a system which automatically detects a list of important targets such as anchor speakers or active politicians in broadcast news videos. This involves several steps including detecting faces in various conditions, associating faces to tracks and identifying whether a face track contains certain faces defined in a watch list. We evaluated this system on a database, which contains about 36 hours of broadcast news videos. Experiments show that our system achieves a very high precision with a reasonable recall rate.",

author = "Hua Gao and Ekenel, {Hazim Kemal} and Rainer Stiefelhagen",

year = "2011",

language = "English",

isbn = "9784901122115",

series = "Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011",

pages = "414--417",

booktitle = "Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011",

note = "12th IAPR Conference on Machine Vision Applications, MVA 2011 ; Conference date: 13-06-2011 Through 15-06-2011",

}

Identifying important people in broadcast news videos. / Gao, Hua; Ekenel, Hazim Kemal; Stiefelhagen, Rainer.
Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011. 2011. p. 414-417 (Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Ekenel, Hazim Kemal

AU - Stiefelhagen, Rainer

PY - 2011

Y1 - 2011

N2 - Automatic face identification in multimedia archives such as broadcast news videos is useful for indexing or retrieving documents based on important persons that appear in the video. In this paper, we propose a system which automatically detects a list of important targets such as anchor speakers or active politicians in broadcast news videos. This involves several steps including detecting faces in various conditions, associating faces to tracks and identifying whether a face track contains certain faces defined in a watch list. We evaluated this system on a database, which contains about 36 hours of broadcast news videos. Experiments show that our system achieves a very high precision with a reasonable recall rate.

AB - Automatic face identification in multimedia archives such as broadcast news videos is useful for indexing or retrieving documents based on important persons that appear in the video. In this paper, we propose a system which automatically detects a list of important targets such as anchor speakers or active politicians in broadcast news videos. This involves several steps including detecting faces in various conditions, associating faces to tracks and identifying whether a face track contains certain faces defined in a watch list. We evaluated this system on a database, which contains about 36 hours of broadcast news videos. Experiments show that our system achieves a very high precision with a reasonable recall rate.

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M3 - Conference contribution

AN - SCOPUS:84872564780

SN - 9784901122115

T3 - Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

SP - 414

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BT - Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

T2 - 12th IAPR Conference on Machine Vision Applications, MVA 2011

Y2 - 13 June 2011 through 15 June 2011

ER -

Identifying important people in broadcast news videos

Abstract

Publication series

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