On Utilising Template and Feature-Based Correspondence in Multi-view Appearance Models

In principle, the recovery and reconstruction of a 3D object from its 2D view projections require the parameterisation of its shape structure and surface re ectance properties. Explicit representation and recovery of such 3D information is notoriously di cult to achieve. Alternatively, a linear combination of 2D views can be used which requires the establishment of dense correspondence between views. This in general, is di cult to compute and necessarily expensive. In this paper we examine the use of a ne and local feature-based transformations in establishing correspondences between very large pose variations. In doing so, we utilise a generic-view template, a generic 3D surface model and Kernel PCA for modelling shape and texture nonlinearities across views. The abilities of both approaches to reconstruct and recover faces from any 2D image are evaluated and compared.

• Type: Conference
• Year: 2000
• Where: ECCV
• Authors: Sami Romdhani, Alexandra Psarrou, Shaogang Gong
• Keywords: 2D Views, Computer Vision, Di Cult, ECCV 2000, Generic 3D Surface, Large Pose Variations, Local Feature-based Transformations