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Springer Tracts in Advanced Robotics
We discuss the problem in which an autonomous vehicle must classify an object based on multiple views. We focus on the active classification setting, where the vehicle controls which views to select to best perform the classification. The problem is formulated as an extension to Bayesian active learning, and we show connections to recent theoretical guarantees in this area. We formally analyze the benefit of acting adaptively as new information becomes available. The analysis leads to adoi:10.1007/978-3-319-29363-9_6 fatcat:hdckjdl5hbbj3l4oef5so6qkva