Volume 4, Number 7, Article 3, Pages 552-563 doi:10.1167/4.7.3 http://journalofvision.org/4/7/3/ ISSN 1534-7362
Junctions and cost functions in motion interpretation
Josh McDermott
Department of Brain and Cognitive Science MIT, Cambridge, MA, USA, & Gatsby Computational Neuroscience Unit,University College, London, London, UK
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Edward H. Adelson
Department of Brain and Cognitive Science MIT, Cambridge, MA, USA
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Abstract

Form, motion, occlusion, and perceptual organization are intimately related. We sought to assess the role of junctions in their interaction. We used stimuli based on a cross moving within an occluding aperture. The two bars of the cross appear to cohere or move separately depending on the context; in accord with prior literature, motion interpretation depends in part on whether the bar endpoints appear to be occluded. To test the importance of junctions in motion interpretation, we explored the effect of changing the junctions generated at the occlusion points in our stimuli, from T-junctions to L-junctions. In some cases, this change had a large effect on perceived motion; in others, it made little difference, suggesting junctions are not the critical variable. Further experiments suggested that what matters is not junctions per se, but whether illusory contours are introduced when the junction category is changed. Our results are consistent with an optimization-based computation that seeks to minimize the presence of illusory contours in the perceptual representation. Although it may be possible to explain our results with interactions between junctions, parsimony favors an explanation in terms of a cost-function operating on layered surface interpretations, with no explicit reference to junctions.

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History
Received July 25, 2002; published July 2, 2004
Citation
McDermott, J., & Adelson, E. H. (2004). Junctions and cost functions in motion interpretation. Journal of Vision, 4(7):3, 552-563, http://journalofvision.org/4/7/3/, doi:10.1167/4.7.3.
Keywords
motion, aperture problem, occlusion, junctions, surface, genericity, mid-level vision, optimization
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