Editors are usually confronted with choosing ONE ideal portrait from a limited set of pictures which represent poses, gestures, and expressions that ALL contribute to define a character. In our view the entire set of a subject's typical portraits should be kept for interactive exhibitions.
A responsive portrait consists of a multiplicity of views whose dynamic presentation results from the interaction between the viewer and the image. The viewer's proximity to the image, head movements, and facial expressions elicit dynamic responses from the portrait, driven by the portrait's own set of autonomous behaviors. This type of interaction reproduces an encounter between two people: the viewer and the character portrayed.
The experience of an individual viewer with the portrait is unique, because it is based on the dynamics of the encounter rather than on the existance of a unique, ideal portrait of the subject. The sensing technology that we used is a computer vision system which tracks the viewer's head movements and facial expressions as she interacts with the digital portrait; therefore, the whole notion of "who is watching who" is reversed: the object becomes the subject, the subject is observed. Face recognition techniques allow the portraited character to keep a record of previous encounters with a visitor and adjust its response based on the history of their interactions.
Nuria Oliver / MIT Media Lab