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This paper presents a non-line-of-sight technique to estimate the position and temperature of an occluded object from a camera via reflection on a wall. Because objects with heat emit far infrared light with respect to their temperature, positions and temperatures are estimated from reflections on a wall. A key idea is that light paths from a hidden object to the camera depend on the position of the hidden object. The position of the object is recovered from the angular distribution of specular and diffuse reflection component, and the temperature of the heat source is recovered from the estimated position and the intensity of reflection. The effectiveness of our method is evaluated by conducting real-world experiments, showing that the position and the temperature of the hidden object can be recovered from the reflection destination of the wall by using a conventional thermal camera.

UV printer, a digital fabrication tool, can print 2D patterns on 3D objects consisting of various materials by using UV inks which immediately dry through being exposed to ultraviolet light. In general use, the translucency of the materials is removed by printing a matte white layer. On the other hand, we propose a method to control the translucency of a printed object by rather utilizing both of the translucency of the materials and inks without printing the white layer. A key is to fuse two different manners: example based and physics based. We apply Kubelka's layer model with few measurements to render the translucency and then build a lookup table between a combination of factors in print and the fabricated translucency. The lookup table is used for finding the best combination to represent an input query about translucency. The rendering method is quantitatively evaluated, and in experiments, we show the proposed system can control the translucency through replicating appearance.

We present a novel time-resolved light transport decomposition method using thermal imaging. Because the speed of heat propagation is much slower than the speed of light propagation, transient transport of far infrared light can be observed at a video frame rate. A key observation is that the thermal image looks similar to the visible light image in an appropriately controlled environment. This implies that conventional computer vision techniques can be straightforwardly applied to the thermal image. We show that the diffuse component in the thermal image can be separated and, therefore, the surface normals of objects can be estimated by the Lambertian photometric stereo. The effectiveness of our method is evaluated by conducting real-world experiments, and its applicability to black body, transparent, and translucent objects is shown.