Audiovisual voice activity detection using off-the-shelf cameras
Sergio Montazzolli, Cláudio R. Jung, Dan Gelb · 2015
This paper presents a new audiovisual voice activity detection (VAD) method for off-the-shelf cameras presenting a color sensor and two microphones. The motion of particles in the mouth region of each face detected by the camera is used as video cue, while the Generalized Cross Correlation with the PHase Transform (GCC-PHAT) is used as audio cue. We then estimate the distribution of the audiovisual cues and perform the final VAD result for each detected face using a Hidden Markov Model (HMM). Experimental results indicated that our method achieves an average 87% accuracy for a set of test videos.