Video-to-Video Face Recognition for Low-Quality Surveillance Data

The availability of video data is an opportunity and a challenge for law enforcement agencies. Face recognition methods can play a key role in the automated search for persons in the data. This work targets efficient representations of low-quality face sequences to enable fast and accurate face sear...

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Bibliographic Details
Main Author: Herrmann, Christian (auth)
Format: Book Chapter
Published: KIT Scientific Publishing 2018
Subjects:
Online Access:Get Fullteks
DOAB: description of the publication
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001 doab_20_500_12854_62070
005 20210212
020 |a KSP/1000083168 
020 |a 9783731507994 
024 7 |a 10.5445/KSP/1000083168  |c doi 
041 0 |a English 
042 |a dc 
100 1 |a Herrmann, Christian  |4 auth 
245 1 0 |a Video-to-Video Face Recognition for Low-Quality Surveillance Data 
260 |b KIT Scientific Publishing  |c 2018 
300 |a 1 electronic resource (IX, 153 p. p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a The availability of video data is an opportunity and a challenge for law enforcement agencies. Face recognition methods can play a key role in the automated search for persons in the data. This work targets efficient representations of low-quality face sequences to enable fast and accurate face search. Novel concepts for multi-scale analysis, dataset augmentation, CNN loss function, and sequence description lead to improvements over state-of-the-art methods on surveillance video footage. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by-sa/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by-sa/4.0/ 
546 |a English 
653 |a face 
653 |a recognition 
653 |a video 
653 |a Videoverarbeitung 
653 |a Gesichtswiederkennung 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/62070  |7 0  |z DOAB: description of the publication