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  1. Outputs

Local deep features for composite face sketch recognition

Conference Paper
Publication Date:
2019
Short description:
Local deep features for composite face sketch recognition / Mendez-Vazquez, H., Becerra-Riera, F., Morales-Gonzalez, A., Lopez-Avila, L., Tistarelli, M.. - (2019), pp. 1-6. (7th International Workshop on Biometrics and Forensics, IWBF 2019 mex 2019) [10.1109/IWBF.2019.8739212].
abstract:
Face sketch recognition is an important task for forensic investigations. In the last decades most of the sketches used by law enforcement agencies are composites made from real photos, using some specialized software. In this work we propose a new method for the automatic recognition of these composite sketches. We propose to use deep learning features extracted from facial components to represent the sketches. We decide to use intermediate layers from already trained deep models and we employ a metric learning approach, as an easier way to learn the differences between sketch and photo domains. The experimental evaluation conducted on two available databases, shows the superiority of the proposal with respect to the use of the original deep models, as well as to other state-of-the-art methods.
Iris type:
4.1 Contributo in Atti di convegno
Keywords:
Composite sketches; face sketch recognition; Local deep learning
List of contributors:
Mendez-Vazquez, H.; Becerra-Riera, F.; Morales-Gonzalez, A.; Lopez-Avila, L.; Tistarelli, M.
Authors of the University:
TISTARELLI Massimo
Handle:
https://iris.uniss.it/handle/11388/228528
Book title:
2019 7th International Workshop on Biometrics and Forensics, IWBF 2019
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http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8735658
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