ABSTRACT
While improved visual realism is known to enhance training effectiveness in virtual surgery simulators, the advances on realistic rendering for these simulators is slower than similar simulations for man-made scenes. One of the main reasons for this is that in vivo data is hard to gather and process. In this paper, we propose the analysis of videolaparoscopy data to compute the Bidirectional Reflectance Distribution Function (BRDF) of living organs as an input to physically based rendering algorithms. From the interplay between light and organic matter recorded in video images, we propose the definition of a process capable of establishing the BRDF for inside-the-body organic surfaces. We present a case study around the liver with patient-specific rendering under global illumination. Results show that despite the limited range of motion allowed within the body, the computed BRDF presents a high-coverage of the sampled regions and produces plausible renderings.
