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Summary: POP: Patchwork of Parts Models for Object
Recognition
Yali Amit
and Alain Trouv´e
January 15, 2007
Yali Amit is with the Department of Statistics and the department of Computer Science, University of
Chicago, Chicago, IL, 60637. Email: amit@marx.uchicago.edu. Supported in part by NSF ITR DMS-
0219016.
Alain Trouv´e is with the CMLA at the Ecole Normale Superieur, Cachan
1
Abstract
We formulate a deformable template model for objects with an efficient mecha-
nism for computation and parameter estimation. The data consists of binary oriented
edge features, robust to photometric variation and small local deformations. The tem-
plate is defined in terms of probability arrays for each edge type. A primary contri-
bution of this paper is the definition of the instantiation of an object in terms of shifts
of a moderate number local submodels - parts - which are subsequently recombined
using a patchwork operation, to define a coherent statistical model of the data. Ob-
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