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
Language
English
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