Decomposing Bag of Words Histograms

Ankit Gandhi, Karteek Alahari, C.V. Jawahar; The IEEE International Conference on Computer Vision (ICCV), 2013, pp. 305-312


We aim to decompose a global histogram representation of an image into histograms of its associated objects and regions. This task is formulated as an optimization problem, given a set of linear classifiers, which can effectively discriminate the object categories present in the image. Our decomposition bypasses harder problems associated with accurately localizing and segmenting objects. We evaluate our method on a wide variety of composite histograms, and also compare it with MRF -based solutions. In addition to merely measuring the accuracy of decomposition, we also show the utility of the estimated object and background histograms for the task of image classification on the PASCAL VOC 2007 dataset.

Related Material

author = {Gandhi, Ankit and Alahari, Karteek and Jawahar, C.V.},
title = {Decomposing Bag of Words Histograms},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {December},
year = {2013}