One of the most serious obstacles to accurate quantification of the underwater motion of a swimmer's body is image deformation caused by refraction. Refraction occurs at the water-air interface plane (glass) owing to the density difference. Camera calibration-reconstruction algorithms commonly used in aquatic research do not have the capability to correct this refraction-induced nonlinear image deformation and produce large reconstruction errors. The aim of this paper is to provide a thorough review of: the nature of the refraction-induced image deformation and its behaviour in underwater object-space plane reconstruction; the intrinsic shortcomings of the Direct Linear Transformation (DLT) method in underwater motion analysis; experimental conditions that interact with refraction; and alternative algorithms and strategies that can be used to improve the calibration-reconstruction accuracy. Although it is impossible to remove the refraction error completely in conventional camera calibration-reconstruction methods, it is possible to improve the accuracy to some extent by manipulating experimental conditions or calibration frame characteristics. Alternative algorithms, such as the localized DLT and the double-plane method are also available for error reduction. The ultimate solution for the refraction problem is to develop underwater camera calibration and reconstruction algorithms that have the capability to correct refraction.

One of the most serious obstacles to accurate quantification of the underwater motion of a swimmer's body is image deformation caused by refraction. Refraction occurs at the water-air interface plane (glass) owing to the density difference. Camera calibration-reconstruction algorithms commonly used in aquatic research do not have the capability to correct this refraction-induced nonlinear image deformation and produce large reconstruction errors. The aim of this paper is to provide a through review of: the nature of the refraction-induced image deformation and its behaviour in underwater object-space plane reconstruction; the intrinsic shortcomings of the Direct Linear Transformation (DLT) method in underwater motion analysis; experimental conditions that interact with refraction; and alternative algorithms and strategies that can be used to improve the calibration-reconstruction accuracy. Although it is impossible to remove the refraction error completely in conventional camera calibration-reconstruction methods, it is possible to improve the accuracy to some extent by manipulating experimental conditions or calibration frame characteristics. Alternative algorithms, such as the localized DLT and the double-plane method are also available for error reduction. The ultimate solution for the refraction problem is to develop underwater camera calibration and reconstruction algorithms that have the capability to correct refraction.

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The purpose of this study was to investigate the effects of transversely sloped ballasted walking surface on gait and rearfoot motion (RFM) parameters. Motion analysis was performed with 20 healthy participants (15 male and 5 female) walking in six surface-slope conditions: two surfaces (solid and ballasted) by three slopes (0, 5, and 10 degrees). The gait parameters (walking velocity, step length, step rate, step width, stance time, and toe-out angle) showed significant surface effect (p= .004) and surface-slope interaction (p= .017). The RFM motion parameters (peak everted/inverted position, eversion/inversion velocity, and acceleration) revealed significant surface (p= .004) and slope (p= .024) effects. The ballasted conditions showed more cautious gait patterns with lower walk velocity, step length, and step rate and longer stance time. In the RFM parameters, the slope effect was more notable in the solid conditions due to the gait adaptations in the ballasted conditions. Ballast conditions showed reduced inversion and increased eversion and RFM range. The RFM data were comparable to other typical walking conditions but smaller than those from running.