Abstract: In order to improve the classification accuracy of the film scene emotion,a novel algorithm was proposed based on the improved fuzzy comprehensive evaluation in the fuzzy mathematics theory by establishing the relationship between the low-level features and high-level cognitive emotion．First,the scene luminance,shot cut rates and color ener-gy were selected as the low-level features for theirs special characteristics that can be used to better distinguish different types of human emotional reaction．Further,the extractive methods were put forward．Secondly,after introducing and improving the fuzzy comprehensive evaluation model,fuzzy membership functions were formed to measure the fuzzy relationship between low-level features and emotion,and then the single factor evaluation matrix was built．Finally,the method of the analytic hierarchy process (AHP) was used to determine the relative weight matrix between the features,and the affective fuzzy feature vector was computed by the improved fuzzy comprehensive evaluation model．And the affective type of the film scene was obtained by the maximization value of the components of the affective fuzzy feature vector and threshold at last．The experimental results show that the proposed algorithm can effectively improve the accuracy of the film affective classification.

Key words: Affective fuzzy feature vector,Fuzzy comprehensive evaluation,Single factor evaluation matrix,Video affective content