Non-uniform sampling of image-based rendering data with the position-interval-error (PIE) function

Abstract

In this paper we study the non-uniform sampling problem for image-based rendering (IBR). We first propose a general position-interval error (PIE) function that can help solve practical sampling problems. We then propose two approaches to capturing IBR data non-uniformly based on PIE, namely progressive capturing (PCAP) and rearranged capturing (RCAP). PCAP is applicable for static scenes. Based on the images captured so far, PCAP determines where to take the next image. RCAP, on the other hand, is for capturing both static and dynamic scenes. The goal is to intelligently arrange the positions of a limited number of cameras such that the final rendering quality is optimal. Experimental results demonstrate that the non-uniform sampling approaches outperform the traditional uniform methods.