Part of
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.
Umfang: IX, 153 S.
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Herrmann, C. 2018. Video-to-Video Face Recognition for Low-Quality Surveillance Data. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000083168
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Veröffentlicht am 3. August 2018
Englisch
182
| Paperback | 978-3-7315-0799-4 |