LEADER 01786nam  2200373z- 450 
001 9910346953203321
005 20210212
010   $a1000083168
035   $a(CKB)4920000000100990
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/62070
035   $a(oapen)doab62070
035   $a(EXLCZ)994920000000100990
100   $a20202102d2018      |y         0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aVideo-to-Video Face Recognition for Low-Quality Surveillance Data
210   $cKIT Scientific Publishing$d2018
215   $a1 online resource (IX, 153 p. p.)
225 1 $aKarlsruher Schriften zur Anthropomatik / Lehrstuhl für Interaktive Echtzeitsysteme, Karlsruher Institut für Technologie ; Fraunhofer-Inst. für Optronik, Systemtechnik und Bildauswertung IOSB Karlsruhe
311 08$a3-7315-0799-4 
330   $aThe 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.
610   $aface
610   $aGesichtswiederkennung
610   $arecognition
610   $avideo
610   $aVideoverarbeitung
700   $aHerrmann$b Christian$4auth$0315734
906   $aBOOK
912   $a9910346953203321
996   $aVideo-to-Video Face Recognition for Low-Quality Surveillance Data$93023514
997   $aUNINA