Based on basic emotion theory and the PAD emotion model that can describe continuous emotion changes, we first propose a more general concept of a five-dimensional emotion model to better meet the needs in the area of emotion recognition. We determined the relationship between its dimensions and basic emotions and used a Pearson correlation analysis, multilayer perceptron, and other methods to compare and verify it with volunteer human identifiers. The results demonstrated that the five-dimensional emotion model was better than human identification in the field of emotion recognition. We also compared it with the PAD emotion model. The results demonstrated that the five-dimensional emotion model performed better. Finally, using the proposed model, we designed a technology prototype of a mood adaptive interface to demonstrate its potential application.