Zobrazeno 1 - 9
of 9
pro vyhledávání: '"SCHLETT, TORSTEN"'
Quality assessment algorithms measure the quality of a captured biometric sample. Since the sample quality strongly affects the recognition performance of a biometric system, it is essential to only process samples of sufficient quality and discard s
Externí odkaz:
http://arxiv.org/abs/2408.11392
Various face image datasets intended for facial biometrics research were created via web-scraping, i.e. the collection of images publicly available on the internet. This work presents an approach to detect both exactly and nearly identical face image
Externí odkaz:
http://arxiv.org/abs/2401.14088
Quality assessment algorithms can be used to estimate the utility of a biometric sample for the purpose of biometric recognition. "Error versus Discard Characteristic" (EDC) plots, and "partial Area Under Curve" (pAUC) values of curves therein, are g
Externí odkaz:
http://arxiv.org/abs/2303.13294
Lossy face image compression can degrade the image quality and the utility for the purpose of face recognition. This work investigates the effect of lossy image compression on a state-of-the-art face recognition model, and on multiple face image qual
Externí odkaz:
http://arxiv.org/abs/2302.12593
Autor:
Schlett, Torsten, Rathgeb, Christian, Henniger, Olaf, Galbally, Javier, Fierrez, Julian, Busch, Christoph
The performance of face analysis and recognition systems depends on the quality of the acquired face data, which is influenced by numerous factors. Automatically assessing the quality of face data in terms of biometric utility can thus be useful to d
Externí odkaz:
http://arxiv.org/abs/2009.01103
Face recognition can benefit from the utilization of depth data captured using low-cost cameras, in particular for presentation attack detection purposes. Depth video output from these capture devices can however contain defects such as holes or gene
Externí odkaz:
http://arxiv.org/abs/2006.11091
Publikováno v:
In Computer Vision and Image Understanding July 2021
Autor:
SCHLETT, TORSTEN1 torsten.schlett@h-da.de, RATHGEB, CHRISTIAN1 christian.rathgeb@h-da.de, HENNIGER, OLAF2 olaf.henniger@igd.fraunhofer.de, GALBALLY, JAVIER3 javier.galbally@ec.europa.eu, FIERREZ, JULIAN4 julian.fierrez@uam.es, BUSCH, CHRISTOPH1 christoph.busch@h-da.de
Publikováno v:
ACM Computing Surveys. 2022 Suppl 10, Vol. 54, p1-49. 49p.
Publikováno v:
2016 International Conference of the Biometrics Special Interest Group (BIOSIG); 2016, p1-4, 4p