Unsupervised Learning of Basic Object Affordances from Object Properties

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Learning human activities and object affordances from RGB-D videos (2012, background): “, 2012) or through observation of the effects of exploratory behaviors (Montesano et al., 2008; Ridge et al., 2009; Moldovan et al., 2012).”
50 Years of object recognition: Directions forward (2013, background): “Recent work on affordances has also focused on its relation to robotics, by building systems that use vision based systems to determine how an object should be grasped and manipulated [131, 132].”