Analysis on the Viewpoint Dependency in 3-D Object Recognition by Support Vector Machines

Authors:
Taichi Hayasaka;Eiichi Ohnishi;Shigeki Nakauchi;Shiro Usui
Affiliations:
-;-;-;-
Venue:
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Bio-inspired Applications of Connectionism-Part II
Year:
2001

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Abstract

In 3-D object recognition in human, the recognition performance across viewpoint changes is divided into 2 types: viewpoint-dependent and viewpoint-invariant. We analyzed the viewpoint dependency of objects under the theory of image-based object representation in human brain (Poggio & Edelman 1990, Tarr 1995) using Support Vector Machines (Vapnik 1995). We suggest from such computational approach that the features of object images between different viewpoints are major factors for human performance in 3-D object recognition.