Abstract
We consider the problem of object classification by exploiting the hierarchy structure of object categories. Our proposed method first train a collection of binary classifiers to differentiate pairs of object categories at different levels of the object hierarchy. Then we use the outputs of these classifiers and the object hierarchy to define a new image representation. Our experimental results show that our proposed method outperforms other baseline methods on several image classification datasets.