A data driven method for feature transformation

M. Dikmen, D. Hoiem, T. S. Huang
2012 2012 IEEE Conference on Computer Vision and Pattern Recognition  
Most image understanding algorithms begin with the extraction of information thought to be relevant to the particular task. This is commonly known as feature extraction and has, up to this date, been a largely manual process, where a reasonable method is chosen through validation on the experimented dataset. In this work we propose a data driven, local histogram based feature extraction method that reduces the manual intervention during the feature computation process and improves on the
more » ... roves on the performance of widely used gradient histogram based features (e.g., HOG). We demonstrate favorable object detection results against HOG on the Inria Pedestrian[7], Pascal 2007[10] data.
doi:10.1109/cvpr.2012.6248069 dblp:conf/cvpr/DikmenHH12 fatcat:z5u5f6h6pvd3rdpsbe3s57lbn4