Surface Enhancement Using Real-Time Photometric Stereo and Reflectance Transformation

Tom Malzbender (HP Labs)
Bennett Wilburn (Microsoft Research Asia)
Dan Gelb (HP Labs)
Bill Ambrisco (Foxhollow Technologies)

Appears in Proceedings of the European Symposium on Rendering 2006

Inspecting an artifact with a real-time photometric stereo and reflectance transformation system.

Abstract

Photometric stereo recovers per-pixel estimates of surface orientation from images of a surface under varying lighting conditions. Transforming reflectance based on recovered normal directions is useful for enhancing the appearance of subtle surface detail. We present the first system that achieves real-time photometric stereo and reflectance transformation. A high-speed camera, computer controlled light sources and fast GPU implementations of the algorithms enable both methods. We also present novel GPU-accelerated normal transformations before relighting that amplify shape detail. By applying standard image processing methods to our computed normal image, we can selectively enhance detail at different frequencies. Our system allows users in fields such as forensics, archaeology and dermatology to investigate objects and surfaces by simply holding them in front of the camera. Real-time analysis of surface roughness for metrology can also be performed from the extracted normal field.

Paper

Adobe Acrobat PDF (7MB)
Citation: Appears in Proceedings of the European Symposium on Rendering 2006 Tomas-Akenin-Moller and Wolfgang Heidrich (Editors). Copyright The Eurographics Association 2006.


Inspecting an artifact with a real-time photometric stereo and reflectance transformation system.
Abstract Photometric stereo recovers per-pixel estimates of surface orientation from images of a surface under varying lighting conditions. Transforming reflectance based on recovered normal directions is useful for enhancing the appearance of subtle surface detail. We present the first system that achieves real-time photometric stereo and reflectance transformation. A high-speed camera, computer controlled light sources and fast GPU implementations of the algorithms enable both methods. We also present novel GPU-accelerated normal transformations before relighting that amplify shape detail. By applying standard image processing methods to our computed normal image, we can selectively enhance detail at different frequencies. Our system allows users in fields such as forensics, archaeology and dermatology to investigate objects and surfaces by simply holding them in front of the camera. Real-time analysis of surface roughness for metrology can also be performed from the extracted normal field.
Paper Adobe Acrobat PDF (7MB) Citation: Appears in Proceedings of the European Symposium on Rendering 2006 Tomas-Akenin-Moller and Wolfgang Heidrich (Editors). Copyright The Eurographics Association 2006.