PT Journal
AU Jon Almazan
   Alicia Fornes
   Ernest Valveny
TI A non-rigid appearance model for shape description and recognition
SO Pattern Recognition
JI PR
PY 2012
BP 3105--3113
VL 45
IS 9
DI 10.1016/j.patcog.2012.01.010
DE Shape recognition; Deformable models; Shape modeling; Hand-drawn recognition
AB In this paper we describe a framework to learn a model of shape variability in a set of patterns. The framework is based on the Active Appearance Model (AAM) and permits to combine shape deformations with appearance variability. We have used two modifications of the Blurred Shape Model (BSM) descriptor as basic shape and appearance features to learn the model. These modifications permit to overcome the rigidity of the original BSM, adapting it to the deformations of the shape to be represented. We have applied this framework to representation and classification of handwritten digits and symbols. We show that results of the proposed methodology outperform the original BSM approach.
ER