Sciweavers

Share
ECCV
1998
Springer

A Probabilistic Approach to Object Recognition Using Local Photometry and Global Geometry

12 years 3 months ago
A Probabilistic Approach to Object Recognition Using Local Photometry and Global Geometry
Many object classes, including human faces, can be modeled as a set of characteristic parts arranged in a variable spatial con guration. We introduce a simpli ed model of a deformable object class and derive the optimal detector for this model. However, the optimal detector is not realizable except under special circumstances (independent part positions). A cousin of the optimal detector is developed which uses \soft" part detectors with a probabilistic description of the spatial arrangement of the parts. Spatial arrangements are modeled probabilistically using shape statistics to achieve invariance to translation, rotation, and scaling. Improved recognition performance over methods based on \hard" part detectors is demonstrated for the problem of face detection in cluttered scenes.
Michael C. Burl, Markus Weber, Pietro Perona
Added 16 Oct 2009
Updated 16 Oct 2009
Type Conference
Year 1998
Where ECCV
Authors Michael C. Burl, Markus Weber, Pietro Perona
Comments (0)
books