Document Type

Book chapter

Source Publication

Statistical and geometrical approaches to visual motion analysis : International Dagstuhl Seminar, Dagstuhl Castle, Germany, July 13-18, 2008

Publication Date

1-1-2009

First Page

235

Last Page

258

Publisher

Springer

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.

DOI

10.1007/978-3-642-03061-1_12

Print ISSN

03029743

Publisher Statement

Copyright © Springer-Verlag Berlin Heidelberg 2009.

Access to external full text or publisher's version may require subscription.

Additional Information

ISBN of the source publication: 9783642030604

Full-text Version

Accepted Author Manuscript

Recommended Citation

Wu, S., Lu, H., Lee, A., & Yuille, A. (2009). Motion integration using competitive priors. In D. Cremers, B. Rosenhahn, A. L. Yuille, & F. R. Schmidt (Eds.), Statistical and geometrical approaches to visual motion analysis: International Dagstuhl Seminar, Dagstuhl Castle, Germany, July 13-18, 2008 (pp. 235-258). Berlin: Springer. doi: 10.1007/978-3-642-03061-1_12