An Ecologically Valid Reference Frame for Perspective Invariant Action Recognition

In robotics, objects and body parts can be represented in various coordinate frames to ease computation. In biological systems, body or body part centered coordinate frames have been proposed as possible reference frames that the brain uses for interacting with the environment. Coordinate transformations are standard tools in robotics and can facilitate perspective invariant action recognition and action prediction based on observed actions of other agents. Although it is known that human adults can do explicit coordinate transformations, it is not clear whether this capability is used for recognizing and understanding the actions of others. Mirror neurons, found in the ventral premotor cortex of macaque monkeys, seem to undertake action understanding in a perspective invariant way, which may rely on lower level perceptual mechanisms. To this end, in this paper we propose a novel reference frame that is ecologically plausible and can sustain basic action understanding and mirror function. We demonstrate the potential of this representation by simulation of an upper body humanoid robot with an action repertoire consisting of push, poke, move-away and bring-to-mouth actions. The simulation experiments indicate that the representation is suitable for action recognition and effect prediction in a perspective invariant way, and thus can be deployed as an artificial mirror system for robotic applications.