From simple innate biases to complex visual concepts.

ABSTRACT: Early in development, infants learn to solve visual problems that are highly challenging for current computational methods. We present a model that deals with two fundamental problems in which the gap between computational difficulty and infant learning is particularly striking: learning to recognize hands and learning to recognize gaze direction. The model is shown a stream of natural videos and learns without any supervision to detect human hands by appearance and by context, as well as direction of gaze, in complex natural scenes. The algorithm is guided by an empirically motivated innate mechanism--the detection of "mover" events in dynamic images, which are the events of a moving image region causing a stationary region to move or change after contact. Mover events provide an internal

SUBMITTER: Ullman S 

PROVIDER: S-EPMC3497814 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature