Abstract
This piece first describes what I see as the significant weaknesses in current un- derstanding of object recognition. We lack good schemes for: using unreliable information — like radiometric measurements — effectively; integrating poten- tially contradictory cues; revising hypotheses in the presence of new information; determining potential representations from data; and suppressing individual dif- ferences to obtain abstract classes. The problems are difficult, but none are unapproachable, given a change of emphasis in our research.
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Forsyth, D. (1999). An Empirical-Statistical Agenda for Recognition. In: Shape, Contour and Grouping in Computer Vision. Lecture Notes in Computer Science, vol 1681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46805-6_2
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DOI: https://doi.org/10.1007/3-540-46805-6_2
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