TY - GEN
T1 - Object predetection based on kernel parametric distribution fitting
AU - Tarel, Jean Philippe
AU - Boughorbel, Sabri
PY - 2006
Y1 - 2006
N2 - Multimodal distribution fitting is an important task in pattern recognition. For instance, the predetection which is the preliminary stage that limits image areas to be processed in the detection stage amounts to the modeling of a multimodal distribution. Different techniques are available for such modeling. We propose a pros and cons analysis of multimodal distribution fitting techniques convenient for object predetection in images. This analysis leads us to propose efficient and accurate variants over the previously proposed techniques as shown by our experiments. These variants are based on parametric distribution fitting in the RKHS space induced by a positive definite kernel.
AB - Multimodal distribution fitting is an important task in pattern recognition. For instance, the predetection which is the preliminary stage that limits image areas to be processed in the detection stage amounts to the modeling of a multimodal distribution. Different techniques are available for such modeling. We propose a pros and cons analysis of multimodal distribution fitting techniques convenient for object predetection in images. This analysis leads us to propose efficient and accurate variants over the previously proposed techniques as shown by our experiments. These variants are based on parametric distribution fitting in the RKHS space induced by a positive definite kernel.
UR - http://www.scopus.com/inward/record.url?scp=34047221965&partnerID=8YFLogxK
U2 - 10.1109/ICPR.2006.883
DO - 10.1109/ICPR.2006.883
M3 - Conference contribution
AN - SCOPUS:34047221965
SN - 0769525210
SN - 9780769525211
T3 - Proceedings - International Conference on Pattern Recognition
SP - 808
EP - 811
BT - Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006
T2 - 18th International Conference on Pattern Recognition, ICPR 2006
Y2 - 20 August 2006 through 24 August 2006
ER -