Conditions that influence the accuracy of anthropometric parameter estimation for human body segments using shape-from-silhouette

Anthropometric parameters are fundamental for a wide variety of applications in biomechanics, anthropology, medicine and sports. Recent technological advancements provide methods for constructing 3D surfaces directly where visual hull construction may be the most cost-effective yet sufficiently accurate method. However, the conditions influencing the accuracy of anthropometric measurements based on visual hull construction are largely unknown. The purpose of this study was to evaluate the conditions that influence the accuracy of shape-from-silhouette reconstruction of body segments dependent on number of cameras, camera resolution and object contours. The results demonstrate that the visual hulls lacked accuracy in concave regions and narrow spaces, but setups with a high number of cameras reconstructed a human form with an average accuracy of less than 1.0mm. In general, setups with less than 8 cameras yielded largely inaccurate visual hull constructions, while setups with 16 and more cameras provided good volume estimations. Body segment volumes were obtained with an average error of 10.5% at a 640x480 resolution using 8 cameras. Changes in resolution did not significantly affect the average error. However, substantial decreases in error were observed with increasing number of cameras (33.3%, 10.5%, 4.1%, and 1.2% using 4, 8, 16, and 64 cameras, respectively).