Simplified Light Probe using Minimal Number of Photodiodes Many display system users have strongly desired that a superimposed virtual object of computer graphics (CG) have optical consistency with a real object at a scene. For this study, we model a realworld light environment as one point light source at infinite distance and an environmental light, which has only three parameters: the point light direction and intensity ratios of the two light sources. We propose a simplified light probe sensor that has five photo IC diodes on each surface of a square pillar, except at its bottom, to estimate the three parameters. The five outputs of the photo IC diode under specific model parameters are obtainable analytically because the directivity characteristics of photo IC diode are approximated as a cosine of the incident angle. The three parameters are then derived from the five outputs. The parameter estimation entails very low computational cost. Experimental results demonstrate sufficient estimation accuracy to render a CG object without a feeling of strangeness.

Rapid Estimation of Optical Properties for SimulationBased Evaluation of Pose Estimation Performance A growing trend in computer vision is the use of synthetic images for the evaluation of computer vision algorithms such as 3D pose estimation. This is partly due to the availability of highquality render engines, which provide highly realistic synthetic images. However, the realism of the rendered images, and thus the reliability of the evaluations, strongly depends on how accurately the scenes are modeled and it requires considerable time and knowledge to do the modeling manually. Automating the modeling process is therefore crucial for making the rendering of photorealistic synthetic images accessible to the wider robotics community. We present a method for automatically modeling object and light properties for rigid, opaque plastic objects commonly found in industry. Our method relies on recordings of the environment captured with a consumer 360mathrmo camera to model the light, and on analysisbysynthesis to estimate the optical properties of the objects. We show that the synthetic images rendered based on our automatic modeling method can be used to predict the overall performance of a monocular 3D pose estimation algorithm.