2:40 PM - 3:00 PM
[1H2-J-13-05] Analysis based on Distributed Representations of Koma Images in Four-scene Comics Story Dataset
Keywords:Comic computation, Image processing
Understanding the creation of human by artificial intelligence (AI) is increasing; however, those are still known as one of the most difficult tasks. In this research, we are challenging for the understanding of four-scene comics by AI. To aim at this challenge, we use a novel dataset what is called “Four-scene Comics Story Dataset", which is the first dataset made by researchers and cartoonists to develop AI creation . We focused on illustration touches of comics which is determined by cartoonists. First, we applied autoencoder (AE) models to this dataset to get distributed representations, then applied classifiers to that and predict a touch. The prediction offers an indirect measure of the distributed representations.
The effectiveness of the proposed method is confirmed by
computer simulations taking data of various pattern of removing parts in koma images of the four-scene comics story dataset structure as an example.
The effectiveness of the proposed method is confirmed by
computer simulations taking data of various pattern of removing parts in koma images of the four-scene comics story dataset structure as an example.