Experimental study of the influence of refraction on underwater three-dimensional reconstruction using the SVP camera model

Abstract

In an underwater imaging system, a perspective camera is often placed outside a tank or in waterproof housing with a flat glass window. The refraction of light occurs when a light ray passes through the water-glass and air-glass interface, rendering the conventional multiple view geometry based on the single viewpoint (SVP) camera model invalid. While most recent underwater vision studies mainly focus on the challenging topic of calibrating such systems, no previous work has systematically studied the influence of refraction on underwater three-dimensional (3D) reconstruction. This paper demonstrates the possibility of using the SVP camera model in underwater 3D reconstruction through theoretical analysis of refractive distortion and simulations. Then, the performance of the SVP camera model in multiview underwater 3D reconstruction is quantitatively evaluated. The experimental results reveal a rather surprising and useful yet overlooked fact that the SVP camera model with radial distortion correction and focal length adjustment can compensate for refraction and achieve high accuracy in multiview underwater 3D reconstruction (within 0.7 mm for an object of dimension 200 mm) compared with the results of land-based systems. Such an observation justifies the use of the SVP camera model in underwater application for reconstructing reliable 3D scenes. Our results can be used to guide the selection of system parameters in the design of an underwater 3D imaging setup.

A Comparative Analysis between Active and Passive Techniques for Underwater 3D Reconstruction of Close-Range Objects

“…In [40] the authors have analysed the refraction effects on the 3D reconstruction by multi-view acquisition, obtaining a minimum accuracy of 0.39 mm in clear water. This value can be compared with our results: with regards to the active technique, the value is the same, while for the passive case it is greater, even if included in the error range of the standard deviation.…”

Refractive Structure-from-Motion Through a Flat Refractive Interface

“…The majority of approaches for underwater 3D reconstruction rely on standard SfM methods assuming the adapted pinhole camera model [12,16], however, this often leads to inaccurate 3D reconstruction [20]. Additionally, systematic geometric bias is present [24] and when the refractive interface is not frontoparallel to the image plane, measurement errors are particularly significant [15].…”

“…This has a strong influence on the image formation process as it invalidates the single view point assumption [10]. While adapting intrinsic camera parameters and distortion coefficients can compensate for refraction it introduces a systematic geometric bias which affects 3D measurements and camera pose estimation [18,16,24] (see Figure 2 (a)). Moreover, if advanced radial basis distortion functions (RBF) are able to compensate for severe and irregular distortions [1,30], refractive distortion directly depends on the depth of the 3D points in the scene [27].…”

Two-View Camera Housing Parameters Calibration for Multi-layer Flat Refractive Interface

“…The refraction effects are either ignored in the early works of underwater computer vision [12], or approximated, such as using focal length adjustment [4,6,9]. However, it is a known fact that the refraction effects are highly non-linear and depends on the scene geometry.…”