Design and Application of Interactive Drawing Teaching System Based on Artificial Intelligence Technology

Abstract

With the rapid development and progress of intelligent technology, interactive painting is facing unprecedented opportunities and challenges. The development of intelligent technology in the field of human–computer interaction has broken through the limits, making the interactive process more humanized, intelligent and diversified, but its creation mechanism has not yet been constructed and is in urgent need of theoretical guidance and normative constraints. To improve the adaptive image generation effect of art painting and enhance the efficiency of painting teaching, this paper proposes an interactive painting teaching system based on artificial intelligence technology. The innovation of this article lies in proposing an improved deep learning based image description generator model on the basis of existing image description generation algorithms based on adaptive attention mechanisms. The model is used to design a block sentinel that controls entity block switching and uses a two-layer LSTM with an improved adaptive attention mechanism as the image description generator. This method effectively improves the efficiency of image generation and enhances teaching efficiency. The experimental results show that the method in this paper can generate image contents accurately.