The 2005 PASCAL Visual Object Classes Challenge

This report presents the results of the 2006 PASCAL Visual Object Classes Challenge (VOC2006). Details of the challenge, data, and evaluation are presented. Participants in the challenge submitted descriptions of their methods, and these have been included verbatim. This document should be considered preliminary, and subject to change.

[1]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[2]  Yan Ke,et al.  PCA-SIFT: a more distinctive representation for local image descriptors , 2004, CVPR 2004.

[3]  Bernt Schiele,et al.  Recognition without Correspondence using Multidimensional Receptive Field Histograms , 2004, International Journal of Computer Vision.

[4]  Martial Hebert,et al.  A spectral technique for correspondence problems using pairwise constraints , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[5]  Fatih Murat Porikli,et al.  Integral histogram: a fast way to extract histograms in Cartesian spaces , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[6]  Jianguo Zhang,et al.  The PASCAL Visual Object Classes Challenge , 2006 .