Audio-based shot classification for audiovisual indexing using PCA, MGD and fuzzy algorithm

An audio-based shot classification method for audiovisual indexing is proposed in this paper. The proposed method mainly consists of two parts, an audio analysis part and a shot classification part. In the audio analysis part, the proposed method utilizes both principal component analysis (PCA) and Mahalanobis generalized distance (MGD). The effective features for the analysis can be automatically obtained by using PCA, and these features are analyzed based on MGD, which can take into account the correlations of the data set. Thus, accurate analysis results can be obtained by the combined use of PCA and MGD. In the shot classification part, the proposed method utilizes a fuzzy algorithm. By using the fuzzy algorithm, the mixing rate of the multiple audio sources can be roughly measured, and thereby accurate shot classification can be attained. Results of experiments performed by applying the proposed method to actual audiovisual materials are shown to verify the effectiveness of the proposed method.