Rigid and non-rigid 3D motion estimation from multiview image sequence

Abstract

Multiviewimagesequenc proccwim has been thefocfi ofcfiVxBFw*jfiO attention inrecVx literature. This paper presents anefficjhw tecjhw*j forobjecxFw*jO rigid and non-rigid 3D motion estimation,applicion to problems ocoblems in multiviewimagesequenc cquen applicwimage MorespecOxj/w*fi a neural network is formed for the estimation of the rigid 3D motion ofeac objec in thescwfiE using initially estimated 2D motion veconw conwFhfixxw* toeac ccfiB view. Non-linear error minimizationtecmizati are adopted for neural network weight update. Furthermore, a novelteclwhfiB is also proposed for the estimation of thelocj non-rigid deformations, based on the multiviewcfixEF geometry. Experimental results using bothstereoscw*fi andtrinochw* crino setups illustrate and evaluate the proposed scosed r 2002 Elsevier Scvier B.V. All rights reserved