The following classical works determine the shape of a transparent object by specularities. In specular stereo [1] a two-camera configuration and image trajectory were used. A theory of specular surface was developed in [16], wherethe relationship between specular surface geometry and image trajectories were studied and features were classified asreal and virtual. Virtual features, which are reflections by a specular surface not limited to highlights, contain useful information on the shape of the object. In [11], two views were used to model the surface of a transparent object, by making use of the optical phenomenon that the degree of polarization of the light reflected from the object surface depends on the reflection angle, which in turn depends on surface normal. This approach utilizing light polarization, where the light transport paths were ray-traced, was further explored in [10] where one camera was used. In [8], a theory was developed on refractive and specular 3D shape by studying the light transport paths, which are restricted to undergo no more than two refractions. Two views were used for dynamic refraction stereo [12] where the notion of refractive disparity was introduced. In this work, a reference pattern and refractive liquid were used. Scatter trace photography [13] was then proposed to reconstruct transparent objects made of inhomogeneous materials, by using a well-calibrated capture device to distinguish direct scatter trace from other indirect optical observations. In [6], a transparent object was immersed into fluorescent liquid. Computer-controlled laser projector and multiview scans were available for merging. While the recovered normal maps of mesostructures look good in [2] and were demonstrated to be useful for relighting, their assumption on specular highlight does not apply to general transparent objects that exhibit complex refraction phenomena (such as totalinternal reflection and caustics). Our shape reconstruction method makes use of rough initial shape (normals), sparse normal cues, and dense specular highlights, which sets itself apart from the above approaches where mathematical theories were developed based on the physics of light transport,or simplifying assumptions were imposed on the transparent object.
The following classical works determine the shape of a transparent object by specularities. In specular stereo [1] a two-camera configuration and image trajectory were used. A theory of specular surface was developed in [16], wherethe relationship between specular surface geometry and image trajectories were studied and features were classified asreal and virtual. Virtual features, which are reflections by a specular surface not limited to highlights, contain useful information on the shape of the object. In [11], two views were used to model the surface of a transparent object, by making use of the optical phenomenon that the degree of polarization of the light reflected from the object surface depends on the reflection angle, which in turn depends on surface normal. This approach utilizing light polarization, where the light transport paths were ray-traced, was further explored in [10] where one camera was used. In [8], a theory was developed on refractive and specular 3D shape by studying the light transport paths, which are restricted to undergo no more than two refractions. Two views were used for dynamic refraction stereo [12] where the notion of refractive disparity was introduced. In this work, a reference pattern and refractive liquid were used. Scatter trace photography [13] was then proposed to reconstruct transparent objects made of inhomogeneous materials, by using a well-calibrated capture device to distinguish direct scatter trace from other indirect optical observations. In [6], a transparent object was immersed into fluorescent liquid. Computer-controlled laser projector and multiview scans were available for merging. While the recovered normal maps of mesostructures look good in [2] and were demonstrated to be useful for relighting, their assumption on specular highlight does not apply to general transparent objects that exhibit complex refraction phenomena (such as totalinternal reflection and caustics). Our shape reconstruction method makes use of rough initial shape (normals), sparse normal cues, and dense specular highlights, which sets itself apart from the above approaches where mathematical theories were developed based on the physics of light transport,or simplifying assumptions were imposed on the transparent object.<br>
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