Video feeling content identification method based on fuzzy comprehensive evaluation

The invention belongs to the field of video content analysis, and in particular relates to a video feeling content identification method based on fuzzy comprehensive evaluation. The prior video feeling content identification method is insufficient in considering the problem of fuzzy attribute of feeling. Aiming at the defects existing in the prior art, the method first uses a fuzzy comprehensive evaluation model in fuzzy theory in the video feeling content identification. Compared with the prior art, the method sufficiently considers the fuzzy attribute of the video feeling content, expresses video clip content by a high-level characteristic vector closely related to feeling based on the fuzzy comprehensive evaluation model, and researches the video feeling content identification in high level; and further, the method adopts an artificial neural network (ANN) to simulate a human feeling response system and identify the video clip to induce basic feeling types generated by audiences. Experiment results verify the effectiveness and feasibility of the method in video feeling content identification.