Automatic highlights extraction for drama video using music emotion and human face features

Abstract

The rich emotion part of a drama video is often the center of attraction to the viewer. Emotion-based highlights extraction is useful for applications such as drama video retrieval and automatic trailer generation. In this paper, we propose a system that uses music emotion and human face as features for automatic extraction of the emotion highlights of a drama video. These high-level audiovisual features are used because music invokes emotion response from the viewer and characters express emotion on their faces. To avoid the interference of speech signal and environmental noise, a novel two-stage music emotion recognition scheme is developed. We first detect the presence of incidental music in a drama video using an audio fingerprint technique, and then perform emotion recognition on the noise-free music available from the album of the incidental music. This simple but effective approach greatly improves the accuracy of music emotion recognition. Besides the conventional subjective evaluation, we propose a new metric for quantitative performance evaluation of highlights extraction. Evaluation results are provided to illustrate the performance of the system.