Detecção de Eventos Sonoros para Sistemas de Segurança

This work aims to investigate different techniques for the classification of atypical sound events, considering the accuracy and classification time, in order to find which of these techniques are most advantageous for surveillance scenarios, minimizing the possibility of relevant events to go unnoticed. LDA, QDA, Decision Tree and KNN techniques were compared. The results obtained indicate that the KNN is the most indicated classification method for the purposes described.