Helmholtz Stereopsis: Exploiting Reciprocity for Surface Reconstruction
Abstract
We present a method — termed Helmholtz stereopsis — for reconstructing the geometry of objects from a collection of images. Unlike most existing methods for surface reconstruction (e.g., stereo vision, structure from motion, photometric stereo), Helmholtz stereopsis makes no assumptions about the nature of the bidirectional reflectance distribution functions (BRDFs) of objects. This new method of multinocular stereopsis exploits Helmholtz reciprocity by choosing pairs of light source and camera positions that guarantee that the ratio of the emitted radiance to the incident irradiance is the same for corresponding points in the two images. The method provides direct estimates of both depth and field of surface normals, and consequently weds the advantages of both conventional and photometric stereopsis. Results from our implementations lend empirical support to our technique.
Cite
Text
Zickler et al. "Helmholtz Stereopsis: Exploiting Reciprocity for Surface Reconstruction." European Conference on Computer Vision, 2002. doi:10.1007/3-540-47977-5_57Markdown
[Zickler et al. "Helmholtz Stereopsis: Exploiting Reciprocity for Surface Reconstruction." European Conference on Computer Vision, 2002.](https://mlanthology.org/eccv/2002/zickler2002eccv-helmholtz/) doi:10.1007/3-540-47977-5_57BibTeX
@inproceedings{zickler2002eccv-helmholtz,
title = {{Helmholtz Stereopsis: Exploiting Reciprocity for Surface Reconstruction}},
author = {Zickler, Todd E. and Belhumeur, Peter N. and Kriegman, David J.},
booktitle = {European Conference on Computer Vision},
year = {2002},
pages = {869-884},
doi = {10.1007/3-540-47977-5_57},
url = {https://mlanthology.org/eccv/2002/zickler2002eccv-helmholtz/}
}