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Semantic person retrieval in surveillance using soft biometrics: AVSS 2018 Challenge II

Semantic person retrieval in surveillance using soft biometrics: AVSS 2018 Challenge II
Semantic person retrieval in surveillance using soft biometrics: AVSS 2018 Challenge II

In surveillance and security today it is a common goal to locate a subject of interest purely from a semantic description; think of an offender description form handed into a law enforcement agency. To date, these tasks are primarily undertaken by operators on the ground either by manually searching a premises or by combing through hours of video footage. Using computer vision to attempt to partially or fully automate these tasks has been gathering interest within the research community in recent years, however, to date there has been little coordinated effort to advance the field. This has motivated the challenge that is presented in this paper: the AVSS Challenge on Semantic Person Retrieval in Surveillance Using Soft Biometrics. This challenge consists of two related tasks: person re-identification from a semantic query and person search within a video from a query. In this paper, we present the publicly available data for this challenge, the evaluation framework, and the challenge results. It is our hope that the outcomes of this challenge and the availability of the data used in this challenge will expedite research and development in this societal field.

IEEE
Halstead, Michael
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Denman, Simon
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Fookes, Clinton
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Tian, Yingli
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Nixon, Mark S.
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Halstead, Michael
0b6a4504-0b17-4c01-9d4d-432cf44f2a95
Denman, Simon
f3f8871a-5268-41c3-816f-de0b49c176c3
Fookes, Clinton
d08f1a73-7438-41d4-8de2-053b2a5b011d
Tian, Yingli
88de5383-3b0e-4b4a-a0ed-8ba01ec3f795
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Halstead, Michael, Denman, Simon, Fookes, Clinton, Tian, Yingli and Nixon, Mark S. (2019) Semantic person retrieval in surveillance using soft biometrics: AVSS 2018 Challenge II. In 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS). IEEE. 6 pp . (doi:10.1109/AVSS.2018.8639379).

Record type: Conference or Workshop Item (Paper)

Abstract

In surveillance and security today it is a common goal to locate a subject of interest purely from a semantic description; think of an offender description form handed into a law enforcement agency. To date, these tasks are primarily undertaken by operators on the ground either by manually searching a premises or by combing through hours of video footage. Using computer vision to attempt to partially or fully automate these tasks has been gathering interest within the research community in recent years, however, to date there has been little coordinated effort to advance the field. This has motivated the challenge that is presented in this paper: the AVSS Challenge on Semantic Person Retrieval in Surveillance Using Soft Biometrics. This challenge consists of two related tasks: person re-identification from a semantic query and person search within a video from a query. In this paper, we present the publicly available data for this challenge, the evaluation framework, and the challenge results. It is our hope that the outcomes of this challenge and the availability of the data used in this challenge will expedite research and development in this societal field.

Full text not available from this repository.

More information

e-pub ahead of print date: November 2018
Published date: 14 February 2019
Venue - Dates: 15th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2018, Auckland, New Zealand, 2018-11-27 - 2018-11-30

Identifiers

Local EPrints ID: 429651
URI: https://eprints.soton.ac.uk/id/eprint/429651
PURE UUID: e069b236-697c-46f6-8a68-07e481b781de
ORCID for Mark S. Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 03 Apr 2019 16:30
Last modified: 20 Jul 2019 01:28

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Contributors

Author: Michael Halstead
Author: Simon Denman
Author: Clinton Fookes
Author: Yingli Tian
Author: Mark S. Nixon ORCID iD

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