Hierarchical neural network classifier for an efficient incident detection based on sound content analysis

A sound content analysis is proposed to detect incident at intersections, which is suitable to implement on hardware such as FPGA. Due to confusion between the sound classes, an hierarchical classifier architecture is proposed to improve the classification performance. The proposed architecture and the feature extraction algorithm are suitable for parallel implementation.