On the Performance of the Intel SR30 Depth Camera: Metrological and Critical Characterization

Specifically conceived for applications related to face analytics and tracking, scene segmentation, hand/finger tracking, gaming, augmented reality, and RGB-D cameras are nowadays used even as 3-D scanners. Despite depth cameras’ accuracy and precision are not comparable with professional 3-D scanners, they still constitute a promising device for reverse engineering (RE) applications in the close range, due to their low cost. This is particularly true for more recent devices, such as, for instance, the RealSense SR300, which promises to be among the best performing close range depth cameras in the market. Given the potentiality of this new device, and since to date a deep investigation on its performances has not been assessed in scientific literature, the main aim of this paper is to characterize and to provide metrological considerations on the Intel RealSense SR300 depth sensor when this is used as a 3-D scanner. To this end, the device sensor performances are first assessed by applying the existing normative guidelines (i.e. the one published by the Association of German Engineers - Verein Deutscher Ingenieure - VDI/VDE 2634) both to a set of raw captured depth data and to a set acquired with optimized setting of the camera. Then, further assessment of the device performances is carried out by applying some strategies proposed in the literature using optimized sensor setting, to reproduce “real life” conditions for the use as a 3-D scanner. Finally, the performance of the device is critically compared against the performance of latest short-range sensors, thus providing a useful guide, for researchers and practitioners, in an informed choice of the optimal device for their own RE application.