Qiang Zhang
ABSTRACT
Recently, deep neural networks have achieved promising performances and become most widely used learning model for prediction applications. However, there are rarely investigations towards animation sentiment analysis through learning models. In this work, we make the first attempt on sentiment analysis of animations through a deep neural network. In contrast with traditional neural networks against real-world images or time-series videos, our model needs to address two primary challenges. Initially, our neural network can dispose the animation images rather than real-world objectives through the iteration of learning process. Subsequently, our model can analyze the sentiment of animation objectives, which can assist animators to modify and enhance the sentiment of videos. From our simulation analysis and comparison results, we can conclude our model can achieve the sentiment analysis of animations with reasonable accuracy and training costs.
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Index Terms
- Research on Animation Sentiment Analysis based on Deep Neural Network
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