Abstract
Abstract. While accuracy, detail, and limited time on site make photogrammetry a valuable means for underwater mapping, the establishment of reference control networks in such settings is oftentimes difficult. In that respect, the use of the coplanarity constraint becomes a valuable solution as it requires neither knowledge of object space coordinates nor setting a reference control network. Nonetheless, imaging in such domains is subjected to non-linear and depth-dependent distortions, which are caused by refractive media that alter the standard single viewpoint geometry. Accordingly, the coplanarity relation, as formulated for the in-air case does not hold in such environment and methods that have been proposed thus far for geometrical modeling of its effect require knowledge of object-space quantities. In this paper we propose a geometrically-driven approach which fulfills the coplanarity condition and thereby requires no knowledge of object space data. We also study a linear model for the establishment of this constraints. Clearly, a linear form requires neither first approximations nor iterative convergence scheme. Such an approach may prove useful not only for object space reconstruction but also as a preparatory step for application of bundle block adjustment and for outlier detection. All are key features in photogrammetric practices. Results show that no unique setup is needed for estimating the relative orientation parameters using the model and that high levels of accuracy can be achieved.
Highlights
Relative orientation enables the estimation of a minimal set of parameters that are necessary to establish coplanarity among corresponding points between two views (Mullen, 2004)
We propose a geometrically driven model that accounts for the refraction effect and constitutes an alternative formulation of the relative orientation and the coplanarity constraint
Results show that a high-level of accuracy is reached while facilitating a flexible orientation strategy for modeling in underwater environments
Summary
Relative orientation enables the estimation of a minimal set of parameters that are necessary to establish coplanarity among corresponding points between two views (Mullen, 2004). Its simplified form, which requires no knowledge of object space coordinates, makes it useful as a means to obtain scene reconstruction, up to a similarity transformation, without setting a reference control network (Stewenius et al, 2006; Pollefeys and Van Gool, 1997; Hemayed, 2003; Hartley and Zisserman, 2003) These advantages become paramount in underwater environments where reference control networks are difficult to establish and where local ones become the more practical solution. The majority of approaches rely on standard in-air models, assuming that the pinhole camera model with distortion can compensate for refraction (e.g., Pizarro et al, 2003; Singh et al, 2007; Shortis, 2015) These models have proved applicable, but analysis of the actual image-point correction due to refraction shows that for. Results show that a high-level of accuracy is reached while facilitating a flexible orientation strategy for modeling in underwater environments
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