Image indexing and content analysis in children’s picture books using a large-scale database

In this paper we introduce a visual database for children’s picture book and we also present an intelligent robot trained on this database. Firstly, a large-scale image dataset is built that contains image samples of book pages. It can be used to verify image indexing algorithms and content recognition algorithms. Secondly, we study the state-of-the-art algorithms in image matching and object recognition. Several approaches are presented and compared from the aspects of computational efficiency and recognition accuracy. In order to improve the speed we proposed a novel hierarchical algorithm for fast search. Finally, using this large-scale database we are able to build a robot that can read children’s picture books and initial experimental results are presented. We can see that both the training database and the algorithms are promising, yet there are still a few open challenges concerning the costs and robustness.