The human visual system makes highly effective use of limited information: it can recognize not only objects, but severely reduced sub-configurations in terms of size or resolution. Minimal images are useful for the interpretation of complex scenes but they are also challenging because by their nature they are non-redundant stimuli. Human studies and computer simulations show that humans and existing models are very different in their ability to interpret minimal images. I will discuss possible implications to the representations used for recognition, brain mechanisms, and algorithms for the interpretation of complex scenes.
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