Semantic pooling for image categorization using multiple kernel learning

In this paper, we propose a new method for taking into account the spatial information in image categorization. More specifically, we remove the loss of spatial information in Bag of Words related methods by computing the image signature over specific regions selected by object detectors. We propose to select the detectors using Multiple Kernel Learning techniques. We carry out experiments on the well known VOC 2007 dataset, and show our semantic pooling obtains promising results.