Using physically Based Rendering to Benchmark Structured Light Scanners

Abstract

Structured light scanning is ubiquituous in 3D acquisition. It is capable of capturing high geometric detail at a low cost under a variety of challenging scene conditions. Recent methods have demonstrated robustness in the presence of artifacts due to global illumination, such as inter-reflections and sub-surface scattering, as well as imperfections caused by projector defocus. For comparing approaches, however, the quantitative evaluation of structured lighting schemes is hindered by the challenges in obtaining ground truth data, resulting in a poor understanding for these methods across a wide range of shapes, materials, and lighting configurations. In this paper, we present a benchmark to study the performance of structured lighting algorithms in the presence of errors caused due to the above properties of the scene. In order to do this, we construct a synthetic structured lighting scanner that uses advanced physically based rendering techniques to simulate the point cloud acquisition process. We show that, under conditions similar to that of a real scanner, our synthetic scanner replicates the same artifacts found in the output of a real scanner. Using this synthetic scanner, we perform a quantitative evaluation of four different structured lighting techniques -gray-code patterns, micro-phase shifting, ensemble codes, and unstructured light scanning. The evaluation, performed on a variety of scenes,demonstrate that no one method is capable of adequately handling all sources of error -each method is appropriate for addressing distinct sources of error.

Rapid Estimation of Optical Properties for Simulation-Based Evaluation of Pose Estimation Performance

“…In the computer vision literature, synthetic images are utilized in a wide range of use cases. They are for instance used in the training of algorithms [2], [3], [4], analysis of uncertainties [5], evaluation of algorithms [1], [6], [7], analysis of visual features [8], [9] and offline programming and prototyping [10], [11]. The methods used for generating the images, the realism of the images and the methods of evaluation differs greatly depending on the use case.…”

“…One of the disadvantages of using rasterization is that some of the subtle interactions between light and material are lost. In order to render images with a high degree of realism, Medeiros et al [1] use a physically based rendering pipeline to simulate a structured light scanner. The synthetic scanner is then used to make a quantitative evaluation of different structured light scanning techniques, taking effects such as subsurface scattering and projector defocus into account.…”

“…Depending on the context, it can be timeconsuming, impractical, or infeasible to capture the needed vision data. Due to the increase in the computational power of modern PCs as well as the improvement of render engines, it has become increasingly popular to rely on synthetic images in addition to real ones [1].…”

Simulation-based Optimization of Camera Placement in the Context of Industrial Pose Estimation

“…In work presented by (Medeiros et al, 2014), structured light scanners are benchmarked in simulation using highly realistic synthetic images. These images are generated using ray tracing which mimics the physical properties of light rays.…”

An Error Analysis of Structured Light Scanning of Biological Tissue

“…Computer simulations of structured light scans were performed in [19] to benchmark encoding methods with respect to various parameters, and were found to have similar robustness with respect to subsurface effects.…”