A Method for Enforcing Integrability in Shape from Shading Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory of Photometric Stereo for a Class of Diffuse Non-Lambertian Surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stereo vision for planetary rovers: stochastic modeling to near real-time implementation
International Journal of Computer Vision
A Bayesian approach to binocular stereopsis
International Journal of Computer Vision
Reflectance and Shape from Images Using a Collinear Light Source
International Journal of Computer Vision
Occlusions and Binocular Stereo
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Variational principles, surface evolution, PDEs, level set methods, and the stereo problem
IEEE Transactions on Image Processing
Modeling the Space of Camera Response Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM SIGGRAPH 2007 courses
Multiflash Stereopsis: Depth-Edge-Preserving Stereo with Small Baseline Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory of Refractive and Specular 3D Shape by Light-Path Triangulation
International Journal of Computer Vision
Color Subspaces as Photometric Invariants
International Journal of Computer Vision
Principles of appearance acquisition and representation
ACM SIGGRAPH 2008 classes
Stereo Image Analysis of Non-Lambertian Surfaces
International Journal of Computer Vision
Shape Recovery of Specular Surface Using Color Highlight Stripe and Light Source Coding
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
Principles of Appearance Acquisition and Representation
Foundations and Trends® in Computer Graphics and Vision
High-accuracy stereo depth maps using structured light
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Shape and materials by example: a photometric stereo approach
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Surface reconstruction via helmholtz reciprocity with a single image pair
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Toward a stratification of helmholtz stereopsis
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Exploiting DLP Illumination Dithering for Reconstruction and Photography of High-Speed Scenes
International Journal of Computer Vision
EGSR'05 Proceedings of the Sixteenth Eurographics conference on Rendering Techniques
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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.