In this paper we present a combined approach for ob-
ject localization and classification. Our contribution is two-
fold. (a) A contextual combination of localization and clas-
sification which shows that classification can improve de-
tection and vice versa. (b) An efficient two stage sliding
window object localization method that combines the effi-
ciency of a linear classifier with the robustness of a sophis-
ticated non-linear one. Experimental results evaluate the
parameters of our two stage sliding window approach and
show that our combined object localization and classifica-
tion methods outperform the state-of-the-art on the PASCAL
VOC 2007 and 2008 datasets.