Adaptive Sparse Representations for recognition of faces and facial attributes
This algorithms has been tested on two different recognition problems:
- Recognition of facial attributes (like expressions, gender, etc.) and
- Face recognition. For the 1) and 2) tasks the reader is referred to our publications  and  respectively. It is the same code but with different parameters. For 1) run demo_eccv2014.m, for 2) run demo_wifs2014.m.
To run ASR+, following Matlab Toolboxes are required:
- demo_eccv2014.m for demo of paper presented at ECCV2004
- demo_wifs2014.m for demo of paper presented at WIFS2004
 D. Mery, K. Bowyer (2014): Recognition of Facial Attributes using Adaptive Sparse Representations of Random Patches. SoftBiometrics Workshop of ECCV2014. Sep. 7th, Zurich. (Best Paper Award)
 Mery, D.; Bowyer K. (2014): [Face Recognition via Adaptive Sparse Representations of Random Patches]http://web.ing.puc.cl/~dmery/Prints/Conferences/International/2014-WIFS-MeryBowyer.pdf, IEEE Workshop on Information Forensics and Security (WIFS 2014), Dec. 3-5, Atlanta.
Copyright 2014 by Group of Machine Intelligence (GRIMA), Department of Computer Science, Universidad Catolica - Chile, and Computer Vision Research Lab, Department of Computer Science and Engineering, University of Notre Dame, Indiana, USA.
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