loading...
Ranklets: Orientation Selective Non-Parametric Features Applied to Face Detection
Quebec City, QC, Canada August 11-August 15
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.104792416th International Conference on Patt ...
 This Article 
 
PDF
HTML
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Fabrizio Smeraldi, Halmstad University
We introduce a family of multiscale, orientation-selective, non-parametric features ("ranklets") Modelled on Haar wavelets. We clarify their relation to the Wilcoxon rank-sum test and the rank transfor and provide an efficient scheme for computation based on the Mann-Whitney statistics. Finally, we show that ranklets outperform other rank features, Haar wavelets, SNoW and linear SVMs (based on independently published results) in face detection experiments over the 24'045 test images in the MIT-CBCL database.
Citation:
Fabrizio Smeraldi, "Ranklets: Orientation Selective Non-Parametric Features Applied to Face Detection," icpr, vol. 3, pp.30379, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 3, 2002
Usage of this product signifies your acceptance of the Terms of Use.