Pose independent object classification from small number of training samples based on kernel principal component analysis of local parts

• Published in: Image and vision computing Vol. 27; no. 9; pp. 1240 - 1251
• Main Author: Hotta, Kazuhiro
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.08.2009
• Subjects: 3D object recognition; Face recognition; Kernel principal component analysis; Local features; Pose independence; Local features; Face recognition; Pose independence; Kernel principal component analysis; 3D object recognition

This paper presents a pose independent classification method from a small number of training samples based on kernel principal component analysis (KPCA) of local parts. Pose changes induce large non-linear variation in feature space of global features. Therefore, conventional methods require multipl...