In this paper, we study the problem of reproducing the world lighting from a single image of an object covered with random specular microfacets on the surface. We show that such reflectors can be interpreted as a randomized mapping from the lighting to the image. Such specular objects have very different optical properties from both diffuse surfaces and smooth specular objects like met als, so we design special imaging system to robustly and effectively photograph them. We present simple yet reliable algorithms to calibrate the proposed system and do the inference. We conduct experiments to verify the correctness of our model assumptions and prove the effectiveness of our pipeline.
The idea that some everyday objects can accidentally serve as a camera has been explored before. It is in shown in @cite_9 that an photograph of a human eye reflects the environment in front of the eye, and this can be used for relighting. In addition, a window or a door can act like a pinhole, in effect imaging the world outside the opening @cite_2 .
@cite_9 @cite_2
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We identify and study two types of “accidental” images that can be formed in scenes. The first is an accidental pinhole camera image. These images are often mistaken for shadows, but can reveal structures outside a room, or the unseen shape of the light aperture into the room. The second class of accidental images are “inverse” pinhole camera images, formed by subtracting an image with a small occluder present from a reference image without the occluder. The reference image can be an earlier frame of a video sequence. Both types of accidental images happen in a variety of different situations (an indoor scene illuminated by natural light, a street with a person walking under the shadow of a building, etc.). Accidental cameras can reveal information about the scene outside the image, the lighting conditions, or the aperture by which light enters the scene. The combination of the cornea of an eye and a camera viewing the eye form a catadioptric (mirror + lens) imaging system with a very wide field of view. We present a detailed analysis of the characteristics of this corneal imaging system. Anatomical studies have shown that the shape of a normal cornea (without major defects) can be approximated with an ellipsoid of fixed eccentricity and size. Using this shape model, we can determine the geometric parameters of the corneal imaging system from the image. Then, an environment map of the scene with a large field of view can be computed from the image. The environment map represents the illumination of the scene with respect to the eye. This use of an eye as a natural light probe is advantageous in many relighting scenarios. For instance, it enables us to insert virtual objects into an image such that they appear consistent with the illumination of the scene. The eye is a particularly useful probe when relighting faces. It allows us to reconstruct the geometry of a face by simply waving a light source in front of the face. Finally, in the case of an already captured image, eyes could be the only direct means for obtaining illumination information. We show how illumination computed from eyes can be used to replace a face in an image with another one. We believe that the eye not only serves as a useful tool for relighting but also makes relighting possible in situations where current approaches are hard to use. We show that walls, and other obstructions with edges, can be exploited as naturally-occurring “cameras” that reveal the hidden scenes beyond them. In particular, we demonstrate methods for using the subtle spatio-temporal radiance variations that arise on the ground at the base of a wall's edge to construct a one-dimensional video of the hidden scene behind the wall. The resulting technique can be used for a variety of applications in diverse physical settings. From standard RGB video recordings, we use edge cameras to recover 1-D videos that reveal the number and trajectories of people moving in an occluded scene. We further show that adjacent wall edges, such as those that arise in the case of an open doorway, yield a stereo camera from which the 2-D location of hidden, moving objects can be recovered. We demonstrate our technique in a number of indoor and outdoor environments involving varied floor surfaces and illumination conditions. When creating a digital composite of two people, it is difficult to exactly match the lighting conditions under which each individual was originally photographed. In many situations, the light source in a scene gives rise to a specular highlight on the eyes. We show how the direction to a light source can be estimated from this highlight. Inconsistencies in lighting across an image are then used to reveal traces of digital tampering.