A probabilistic model of gaze imitation and shared attention

An important component of language acquisition and cognitive learning is gaze imitation. Infants as young as one year of age can follow the gaze of an adult to determine the object the adult is focusing on. The ability to follow gaze is a precursor to shared attention, wherein two or more agents simultaneously focus their attention on a single object in the environment. Shared attention is a necessary skill for many complex, natural forms of learning, including learning based on imitation. This paper presents a probabilistic model of gaze imitation and shared attention that is inspired by Meltzoff and Moore's AIM model for imitation in infants. Our model combines a probabilistic algorithm for estimating gaze vectors with bottom-up saliency maps of visual scenes to produce maximum a posteriori (MAP) estimates of objects being looked at by an observed instructor. We test our model using a robotic system involving a pan-tilt camera head and show that combining saliency maps with gaz...

• Type: Journal
• Year: 2006
• Where: NN
• Authors: Matthew W. Hoffman, David B. Grimes, Aaron P. Shon, Rajesh P. N. Rao
• Keywords: Gaze, Neural Networks, NN 2006, Probabilistic Models, Saliency Maps