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.

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