Motion integration using competitive priors

Shuang WU, Hongjing LU, Lap Fai, Alan LEE, Alan YUILLE

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Abstract

Psychophysical experiments show that humans are better at perceiving rotation and expansion than translation [5][9]. These findings are inconsistent with standard models of motion integration which predict best performance for translation. To explain this discrepancy, our theory formulates motion perception at two levels of inference: we first perform model selection between the competing models (e.g. translation, rotation, and expansion) and then estimate the velocity using the selected model. We define novel prior models for smooth rotation and expansion using techniques similar to those in the slow-and-smooth model [23] (e.g. Green functions of differential operators). The theory gives good agreement with the trends observed in four human experiments.
Original languageEnglish
Title of host publicationStatistical and geometrical approaches to visual motion analysis : International Dagstuhl Seminar, Dagstuhl Castle, Germany, July 13-18, 2008
PublisherSpringer
Pages235-258
Number of pages24
ISBN (Print)9783642030604
DOIs
Publication statusPublished - 1 Jan 2009
Externally publishedYes

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WU, S., LU, H., LEE, L. F. A., & YUILLE, A. (2009). Motion integration using competitive priors. In Statistical and geometrical approaches to visual motion analysis : International Dagstuhl Seminar, Dagstuhl Castle, Germany, July 13-18, 2008 (pp. 235-258). Springer. https://doi.org/10.1007/978-3-642-03061-1_12