Spatial extensions to bag of visual words
Ville Viitaniemi, Jorma T. Laaksonen · 2009
The Bag of Visual Words (BoV) paradigm has successfully been applied to image content analysis tasks such as image classification and object detection. The basic BoV approach overlooks spatial descriptor distribution within images. Here we describe spatial extensions to BoV and experimentally compare them in the VOC2007 benchmark image category detection task. In particular, we compare two ways for tiling images geometrically: soft tiling approach---proposed here---and the traditional hard tiling technique. The experiments also address two methods of fusing information from several tilings of the images: post-classifier fusion and fusion on the level of a SVM kernel.