Reconstructing Relief Surfaces

Abstract

This paper generalizes Markov Random Field (MRF) stereo methods to the generation of surface relief (height) fields rather than disparity or depth maps. This generalization enables the reconstruction of complete object models using the same algorithms that have been previously used to compute depth maps in binocular stereo. In contrast to traditional dense stereo where the parametrization is image based, here we advocate a parametrization by a height field over any base surface. In practice, the base surface is a coarse approximation to the true geometry, e.g., a bounding box, visual hull or triangulation of sparse correspondences, and is assigned or computed using other means. A dense set of sample points is defined on the base surface, each with a fixed normal direction and unknown height value. The estimation of heights for the sample points is achieved by a belief propagation technique. Our method provides a viewpoint independent smoothness constraint, a more compact parametrization and explicit handling of occlusions. We present experimental results on real scenes as well as a quantitative evaluation on an artificial scene.

On the relationship between multi-view data capturing and quality of rendered virtual view

“…13 But the ideal sampling rate of spectral support is hard to meet in practice. Sometimes insufficient image sampling rate needs to be compensated by means such as geometry sampling.…”

Three-dimensional surface imaging by multi-frequency phase shift profilometry with angle and pattern modeling for system calibration

“…As a result, non-contact 3D surface imaging technology advances rapidly and greatly in the past decades with the stimulation of market demands in industrial community, medical applications and scientific research. The non-contact 3D surface imaging techniques include two main categories based on the reflective characteristics of the surface: (1) techniques to measure the specular surfaces [1][2][3][4][5], and (2) techniques to measure the diffuse surfaces [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. Among them, phase shift profilometry is the most popular method due to its overall higher measurement accuracy and measurement efficiency compared to other non-contact 3D surface imaging techniques.…”