Augmenting Bag-of-Words - Category Specific Features and Concept Reasoning

In this paper we present our approach to the 2010 ImageClef PhotoAnnotation task. Based on the well-known bag-of-words approach we suggest two extensions. First, we analyzed the impact of category specific features and classifiers. In order to classify quality-related image categories we implemented a sharpness measure and use this as additional feature in the classification process. Second, we propose a postclassification step, which is based on the observation that many of the categories should be considered as being related to each other: Some categories exclude or allow for inference to others. We incorporate inference and exclusion rules by refining the classification results. The results we obtain show that both extensions can provide a classification performance increase when compared the the standard BoW approach.