Context Aware Image Annotation in Active Learning with Batch Mode

Bags are not isolated in the Multiple-Instance Active Learning process, especially for image as bag, because each picture has its inherent background or metainformation, such as its taken time, taken place, the topic, and they have possible associations. With context associations, we can build the annotation tool providing more interactively user experience and thus increase the annotation efficiency. In this paper, we propose a context aware images annotation framework that selects the images that are context related to query in the multiple-instance active learning with batch mode. Experiments show that it takes less time for annotation with the proposed framework compared to traditional ones, and improve the labeling efficiency.