Abstract
We propose a method for analyzing photometric factors, such as diffuse reflection, specular reflection, attached shadow, and cast shadow. For analyzing real images, we utilize the photometric linearization method, which was originally proposed for image synthesis. First, we show that each pixel can be photometrically classified by a simple comparison of the pixel intensity. Our classification algorithm requires neither 3D shape information nor color information of the scene. Then, we show that the accuracy of the photometric linearization can be improved by introducing a new classification-based criterion to the linearization process. Experimental results show that photometric factors can be correctly classified without any special devices. A further experiment shows that the proposed method is effective for photometric stereo.
| Original language | English |
|---|---|
| Pages (from-to) | 3326-3334 |
| Number of pages | 9 |
| Journal | Journal of the Optical Society of America A: Optics and Image Science, and Vision |
| Volume | 24 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - 2007 |
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ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Computer Vision and Pattern Recognition
Cite this
Analysis of photometric factors based on photometric linearization. / Mukaigawa, Yasuhiro; Ishii, Yasunori; Shakunaga, Takeshi.
In: Journal of the Optical Society of America A: Optics and Image Science, and Vision, Vol. 24, No. 10, 2007, p. 3326-3334.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Analysis of photometric factors based on photometric linearization
AU - Mukaigawa, Yasuhiro
AU - Ishii, Yasunori
AU - Shakunaga, Takeshi
PY - 2007
Y1 - 2007
N2 - We propose a method for analyzing photometric factors, such as diffuse reflection, specular reflection, attached shadow, and cast shadow. For analyzing real images, we utilize the photometric linearization method, which was originally proposed for image synthesis. First, we show that each pixel can be photometrically classified by a simple comparison of the pixel intensity. Our classification algorithm requires neither 3D shape information nor color information of the scene. Then, we show that the accuracy of the photometric linearization can be improved by introducing a new classification-based criterion to the linearization process. Experimental results show that photometric factors can be correctly classified without any special devices. A further experiment shows that the proposed method is effective for photometric stereo.
AB - We propose a method for analyzing photometric factors, such as diffuse reflection, specular reflection, attached shadow, and cast shadow. For analyzing real images, we utilize the photometric linearization method, which was originally proposed for image synthesis. First, we show that each pixel can be photometrically classified by a simple comparison of the pixel intensity. Our classification algorithm requires neither 3D shape information nor color information of the scene. Then, we show that the accuracy of the photometric linearization can be improved by introducing a new classification-based criterion to the linearization process. Experimental results show that photometric factors can be correctly classified without any special devices. A further experiment shows that the proposed method is effective for photometric stereo.
UR - http://www.scopus.com/inward/record.url?scp=36949030692&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=36949030692&partnerID=8YFLogxK
U2 - 10.1364/JOSAA.24.003326
DO - 10.1364/JOSAA.24.003326
M3 - Article
C2 - 17912327
AN - SCOPUS:36949030692
VL - 24
SP - 3326
EP - 3334
JO - Journal of the Optical Society of America. A, Optics and image science
JF - Journal of the Optical Society of America. A, Optics and image science
SN - 1084-7529
IS - 10
ER -