Identificação de atividade de voz baseada em vídeo

Abstract

Currently, there are several works with many di_erent approaches to image processing for detection of voice activity (VAD). Its applications cross over di_erent areas, such as voice commands in vehicles and videoconferencing. The motivation of this work consists in building an algorithm that contributes to the improvement of techniques image processing applied to detect voice activity on video. The issue already presents a great diversity of approaches. However, the focus of this work lies in _nding alternatives to improve the extraction of a skin and non-skin color model and, from there, extract a classi_er to identify the activity of speech more accurately. Existing algorithms of face detection and classi_cation of the lips were used and improved. Through the creation of patches under the eyes, a model was created to determine the individual characteristics of skin color using the mean and standard deviation of the pixels of the patches and the mouth area. The results are presented based on two approaches.