TY  - CONF
AU  - E. Royer
AU  - J. Chazalon
AU  - Marçal Rusiñol
AU  - F. Bouchara
A2  - ICDAR
PY  - 2017//
TI  - Benchmarking Keypoint Filtering Approaches for Document Image Matching
BT  - 14th International Conference on Document Analysis and Recognition
N2  - Best Poster Award.Reducing  the  amount  of  keypoints  used  to  index an  image  is particularly  interesting  to  control  processing  time and   memory   usage   in   real-time   document   image   matching applications,  like  augmented  documents  or  smartphone  applications. This paper benchmarks two keypoint selection methods on  a  task  consisting  of  reducing  keypoint  sets  extracted  from document  images,  while  preserving  detection  and segmentation accuracy. We first study the different forms of keypoint filtering, and  we  introduce  the  use  of  the  CORE  selection  method  onkeypoints  extracted  from  document  images.  Then,  we  extend  a previously published benchmark by including evaluations of the new  method,  by  adding  the  SURF-BRISK  detection/description scheme,  and  by  reporting  processing  speeds.  Evaluations  are conducted   on   the   publicly   available   dataset   of   ICDAR2015 SmartDOC  challenge  1.  Finally,  we  prove  that  reducing  the original  keypoint  set  is  always  feasible  and  can  be  beneficialnot  only  to  processing  speed  but  also  to  accuracy.
L1  - http://refbase.cvc.uab.es/files/RCR2017.pdf
UR  - http://dx.doi.org/10.1109/ICDAR.2017.64
N1  - DAG; 600.084; 600.121
ID  - E. Royer2017
ER  -