GPVC: Graphics Pipeline-Based Visibility Classification for Texture Reconstruction

Abstract

The shadow-mapping and ray-tracing algorithms are the two popular approaches used in visibility handling for multi-view based texture reconstruction. Visibility testing based on the two algorithms needs a user-defined bias to reduce computation error. However, a constant bias does not work for every part of a geometry. Therefore, the accuracy of the two algorithms is limited. In this paper, we propose a high-precision graphics pipeline-based visibility classification (GPVC) method without introducing a bias. The method consists of two stages. In the first stage, a shader-based rendering is designed in the fixed graphics pipeline to generate initial visibility maps (IVMs). In the second stage, two algorithms, namely, lazy-projection coverage correction (LPCC) and hierarchical iterative vertex-edge-region sampling (HIVERS), are proposed to classify visible primitives into fully visible or partially visible primitives. The proposed method can be easily implemented in the graphics pipeline to achieve parallel acceleration. With respect to efficiency, the proposed method outperforms the bias-based methods. With respect to accuracy, the proposed method can theoretically reach a value of 100%. Compared with available libraries and software, the textured model based on our method is smoother with less distortion and dislocation.

Color and Laser Data as a Complementary Approach for Heritage Documentation

“…However, since both approaches perform pixel-by-pixel tasks, a considerable amount of computer memory and costly computation time are required. Moreover, if the image and model resolutions are not compatible, the results may have pseudo-visibility and incorrect occlusion [56]. Because of these limitations, many innovative frameworks and algorithms have been developed to improve their performance.…”

“…Abovementioned methods, Z-buffer and ray tracing, show drawback and low performance on complex surfaces [56]. They have a high cost of computation incurred in pixel-by-pixel neighborhood searching, which further needs iteration processing to address intersection points between the rays and the DSM.…”