Title :
From Intensity Profile to Surface Normal: Photometric Stereo for Unknown Light Sources and Isotropic Reflectances
Author :
Feng Lu ; Matsushita, Yasuyuki ; Sato, Imari ; Okabe, Takahiro ; Sato, Yoichi
Author_Institution :
Inst. of Ind. Sci., Univ. of Tokyo, Tokyo, Japan
Abstract :
We propose an uncalibrated photometric stereo method that works with general and unknown isotropic reflectances. Our method uses a pixel intensity profile, which is a sequence of radiance intensities recorded at a pixel under unknown varying directional illumination. We show that for general isotropic materials and uniformly distributed light directions, the geodesic distance between intensity profiles is linearly related to the angular difference of their corresponding surface normals, and that the intensity distribution of the intensity profile reveals reflectance properties. Based on these observations, we develop two methods for surface normal estimation; one for a general setting that uses only the recorded intensity profiles, the other for the case where a BRDF database is available while the exact BRDF of the target scene is still unknown. Quantitative and qualitative evaluations are conducted using both synthetic and real-world scenes, which show the state-of-the-art accuracy of smaller than 10 degree without using reference data and 5 degree with reference data for all 100 materials in MERL database.
Keywords :
brightness; differential geometry; photometry; photoreflectance; stereo image processing; BRDF database; MERL database; directional illumination; general isotropic materials; geodesic distance; intensity profile distribution; isotropic reflectances; pixel intensity profile; radiance intensities sequence; reflectance properties; surface normal estimation; uncalibrated photometric stereo method; uniformly distributed light directions; Databases; Light sources; Lighting; Linearity; Materials; Matrix decomposition; Sparse matrices; BRDF; Uncalibrated photometric stereo; general reflectance; intensity profile;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2015.2389841