Abstract
When a picture book is photographed with a smart device, the text is analyzed for meaning and associated images are created. Image creation is the first step in learning DCGAN using class lists and images. In this study, DCGAN was trained with 11 classes and images of 1688 bears, which were collected by ImageNet for design. The second step is to shoot the image and text of the picture book on a smart device, and convert the text part of the shot image into a system readable character. We use the morpheme analyzer to classify nouns and verbs in text, and Discriminator learn to recognize the classified parts of speech as latent vectors of images. The third step is to create an associated image in the text. In the picture book, take the text of the part without the image and extract nouns and verbs. The extracted parts of speech and the learned latent vector are used as Generator parameters to generate images associated with the text.
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References
Kim, I.-T., Yoo, K.-J.: Effects of augmented reality picture book on the language expression and flow of young children’s in picture book reading activities. J. Korea Open Assoc. Early Child. Educ. 23(1), 83–109 (2018)
Ryu, K.M., Kim, H.J., Kim, H.J., Lee, E.J.I., Heo, J.Y.: A development of interactive storybook with digital board and smart device. 한국HCI학회 학술대회, pp. 1179–1182 (2017)
Kim, Y., Park, H.: Study on the relation between young children’s smart device immersion tendency and their playfulness. Early Child. Educ. Res. Rev. 20(4), 337–353 (2016)
Lee, G.-C., Yoo, J.: Development an Android based OCR Application for Hangul Food Menu. J. Korea Inst. Inf. Commun. Eng. 21(5), 951–959 (2017)
Smith, R.: An overview of the tesseract OCR engine. In: Ninth International Conference on Document Analysis and Recognition (ICDAR 2007), Parana, pp. 629–633 (2007)
Park, E.L., Cho, S.: KoNLPy: Korean natural language processing in Python. In: Proceedings of the 26th Annual Conference on Human & Cognitive Language Technology, pp. 133–136 (2014)
Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv:1511.06434 (2015)
Han, Y., Kim, H.J.: Face morphing using generative adversarial networks. J. Digital Contents Soc. 19(3), 435–443 (2018)
Reed, S., Akata, Z., Yan, X., Logeswaran, L., Schiele, B., Lee, H.: Generative adversarial text to image synthesis. In: Proceedings of the 33rd International Conference on Machine. Learning, New York, NY, USA, 2016, JMLR: W & CP, vol. 48 (2016)
Springenberg, J.T., Dosovitskiy, A., Brox, T., Riedmiller, M.: Striving for simplicity: the all convolutional net. In: Proceedings of the International Conference on Learning Representations, pp. 1–14, arXiv preprint arXiv:1412.6806 (2015)
Reed, S., Akata, Z., Yan, X., Logeswaran, L., Schiele, B., Lee, H.: Proceedings of The 33rd International Conference on Machine Learning, PMLR, vol. 48, pp. 1060–1069 (2016)
Triantafyllidou, D., Tefas, A.: Face detection based on deep convolutional neural networks exploiting incremental facial part learning. In: Proceeding of the International Conference on Pattern Recognition, pp. 3560–3565 (2016)
Miller, E.L., Huang, G., RoyChowdhury, A., Li, H., Hua, G.: Labeled faces in the wild: a survey. In: Kawulok, M., Celebi, M., Smolka, B. (eds.) Advances in Face Detection and Facial Image Analysis, pp. 189–248 (2016)
Acknowledgments
This work has supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2017R1A2B4008886).
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Cho, J., Moon, N. (2020). Design of Image Generation System for DCGAN Based Picture Book Text. In: Park, J., Park, DS., Jeong, YS., Pan, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2018 2018. Lecture Notes in Electrical Engineering, vol 536. Springer, Singapore. https://doi.org/10.1007/978-981-13-9341-9_46
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DOI: https://doi.org/10.1007/978-981-13-9341-9_46
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