### 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 language | English |
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Title of host publication | Statistical and geometrical approaches to visual motion analysis : International Dagstuhl Seminar, Dagstuhl Castle, Germany, July 13-18, 2008 |

Publisher | Springer |

Pages | 235-258 |

Number of pages | 24 |

ISBN (Print) | 9783642030604 |

DOIs | |

Publication status | Published - 1 Jan 2009 |

Externally published | Yes |

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## Cite this

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