Detecting bids for eye contact using a wearable camera

We propose a system for detecting bids for eye contact directed from a child to an adult who is wearing a point-of-view camera. The camera captures an egocentric view of the child-adult interaction from the adult´s perspective. We detect and analyze the child´s face in the egocentric video in order to automatically identify moments in which the child is trying to make eye contact with the adult. We present a learning-based method that couples a pose-dependent appearance model with a temporal Conditional Random Field (CRF). We present encouraging findings from an experimental evaluation using a newly collected dataset of 12 children. Our method outperforms state-of-the-art approaches and enables measuring gaze behavior in naturalistic social interactions.