A Neural Multi-expert Classification System for MPEG Audio Segmentation

The current research efforts in the field of video parsing and analysis are mainly focused on the use of pictorial information, while neglecting an important supplementary source of content information such as the embedded audio or soundtrack. In contrast, in this paper we address the issue of exploiting audio information that can be jointly used with video information for scene changes detection. The proposed method directly works on MPEG encoded sequences so to avoid computationally intensive decoding procedures. It is based on a multi-expert classification system made up of a hierarchical ensemble of neural networks. Finally, after presentation of a large audio database, suitably designed for assessing the performance of the approach, preliminary experimental results are discussed.

• Type: Conference
• Year: 2001
• Where: ICAPR
• Authors: Massimo De Santo, Gennaro Percannella, Carlo Sansone, Mario Vento
• Keywords: Current Research Efforts, ICAPR 2001, Important Supplementary Source, MPEG Encoded Sequences, Pattern Recognition