Optimising Camera–ChArUco Geometry for Motion Compensation in Standing Equine CT: A CT-Motivated Benchtop Study

Standing equine computed tomography (CT) acquisitions are susceptible to residual postural sway, which can introduce view-inconsistent motion and degrade image quality. External optical tracking based on ChArUco fiducials is a promising, low-cost strategy to enable projection-wise motion compensation, yet quantitative guidance on how camera–marker geometry affects pose-estimation performance remains limited. This CT-motivated benchtop study characterizes how the relative camera–ChArUco configuration influences both the accuracy (bias with respect to ground truth) and the precision (repeatability) of pose estimates obtained from RGB images using OpenCV ChArUco detection and reprojection-error minimization to estimate the rigid camera-to-board transformation. Controlled experiments systematically varied acquisition protocol (continuous repeated estimates at fixed pose versus cyclic repositioning), viewing angle over a wide angular range at two working distances, and camera-to-board distance over multiple depth settings. Ground truth for angular configurations was defined by a stepper-motor rotation stage, while distance ground truth was obtained by ruler measurements. Performance was summarized via mean absolute error and standard deviation across repeated measurements, complemented by variance-based statistical testing with multiple-comparison correction. Cyclic repositioning did not yield evidence of increased variability relative to continuous acquisitions, supporting view-by-view sampling. Viewing angle induced a consistent accuracy–precision trade-off for rotations: frontal views minimized mean error but exhibited higher variability, whereas oblique views reduced jitter at the expense of increased bias. Increasing working distance reduced repeatability, most prominently for depth-related components. Overall, these findings provide pre-clinical guidance for selecting camera/marker placement (moderately oblique viewpoints, limited working distance, sufficient image footprint) before in-scanner and in-vivo validation for standing equine CT motion compensation.