Cue-based equivalence classes and incremental discrimination for multi-cue recognition of “interactionable” objects

There is a subset of objects for which interaction can provide numerous cues to those objects´ identity. Robots are often in situations where they can take advantage being able to observe humans interacting with the objects. In this paper, we define this subset of ´interactionable´ objects for which we use our multiple-cue object recognition algorithm (MCOR) to take advantage of using multiple cues. We present two main contributions: 1) the introduction of cue-driven equivalence class discrimination, and 2) the integration of this technique, the general MCOR algorithm, and a hierarchical activity recognition algorithm also presented in this paper, demonstrated on data taken from a static Sony QRIO robot observing a human interacting with objects. The hierarchical activity recognition provides an important cue for the object recognition.