Title :
View invariant object recognition
Author :
Srestasathiern, Panu ; Yilmaz, Alper
Author_Institution :
Photogrammetric Comput. Vision Lab., Ohio State Univ., Columbus, OH, USA
Abstract :
This paper introduces a method for the recognition planar objects under projective geometry. Our method is based on a similarity measure invariant to projective transform. The proposed similarity measure utilizes the distribution of the projective relations between the conic section pairs, which are estimated from the object¿s shape. We conjecture that given two objects of the same type, which are viewed from different viewpoints generate similar histograms, such that their difference is smaller than the histograms generated from other object types. The proposed measure has shown promising performance on the Brown shape database.
Keywords :
computational geometry; object recognition; shape recognition; statistical analysis; transforms; conic section pair; histogram; object shape estimation; projective geometry; projective relation distribution; projective transform; similarity measure; view invariant planar object recognition; Application software; Computer vision; Equations; Geometry; Histograms; Image databases; Layout; Object recognition; Shape measurement; Symmetric matrices;
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
DOI :
10.1109/ICPR.2008.4761238