| Item type |
Trans(1) |
| 公開日 |
2005-06-15 |
| タイトル |
|
|
タイトル |
Illumination Color and Intrinsic Surface Properties-Physics-based Color Analyses from a Single Image |
| タイトル |
|
|
言語 |
en |
|
タイトル |
Illumination Color and Intrinsic Surface Properties-Physics-based Color Analyses from a Single Image |
| 言語 |
|
|
言語 |
jpn |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
テクニカルノート（IPSJ Best Paper Award、論文賞受賞） |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 著者所属 |
|
|
|
Australian National University |
| 著者所属 |
|
|
|
The University of Tokyo |
| 著者所属(英) |
|
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|
en |
|
|
Australian National University |
| 著者所属(英) |
|
|
|
en |
|
|
The University of Tokyo |
| 著者名 |
RobbyT.Tan
Katsushi, Ikeuchi
|
| 著者名(英) |
Robby, T.Tan
Katsushi, Ikeuchi
|
| 論文抄録 |
|
|
内容記述タイプ |
Other |
|
内容記述 |
In the real world the color appearances of objects are generally not consistent. It depends principally on two factors: illumination spectral power distribution (illumination color) and intrinsic surface properties. Consequently to obtain objects’ consistent color descriptors we have to deal with those two factors. The former is commonly referred to as color constancy: a capability to estimate and discount the illumination color while the latter is identical to the problem of recovering body color from highlights. This recovery is crucial because highlights emitted from opaque inhomogeneous objects can cause the surface colors to be inconsistent with regard to the change of viewing and illuminant directions. We base our color constancy methods on analyzing highlights or specularities emitted from opaque inhomogeneous objects. We have successfully derived a linear correlation between image chromaticity and illumination chromaticity. This linear correlation is clearly described in inverse-intensity chromaticity space a novel two-dimensional space we introduce. Through this space we become able to effectively estimate illumination chromaticity (illumination color) from both uniformly colored surfaces and highly textured surfaces in a single integrated framework thereby making our method significantly advanced over the existing methods. Meanwhile for separating reflection components we propose an approach that is based on an iterative framework and a specularfree image. The specular-free image is an image that is free from specularities yet has different body color from the input image. In general the approach relies principally on image intensity and color. All methods of color constancy and reflection-components separation proposed in this paper are analyzed based on physical phenomena of the real world making the estimation more accurate and have strong basics of analysis. In addition all methods require only a single input image. This is not only practical but also challenging in term of complexity. |
| 論文抄録(英) |
|
|
内容記述タイプ |
Other |
|
内容記述 |
In the real world, the color appearances of objects are generally not consistent. It depends principally on two factors: illumination spectral power distribution (illumination color) and intrinsic surface properties. Consequently, to obtain objects’ consistent color descriptors, we have to deal with those two factors. The former is commonly referred to as color constancy: a capability to estimate and discount the illumination color, while the latter is identical to the problem of recovering body color from highlights. This recovery is crucial because highlights emitted from opaque inhomogeneous objects can cause the surface colors to be inconsistent with regard to the change of viewing and illuminant directions. We base our color constancy methods on analyzing highlights or specularities emitted from opaque inhomogeneous objects. We have successfully derived a linear correlation between image chromaticity and illumination chromaticity. This linear correlation is clearly described in inverse-intensity chromaticity space, a novel two-dimensional space we introduce. Through this space, we become able to effectively estimate illumination chromaticity (illumination color) from both uniformly colored surfaces and highly textured surfaces in a single integrated framework, thereby making our method significantly advanced over the existing methods. Meanwhile, for separating reflection components, we propose an approach that is based on an iterative framework and a specularfree image. The specular-free image is an image that is free from specularities yet has different body color from the input image. In general, the approach relies principally on image intensity and color. All methods of color constancy and reflection-components separation proposed in this paper are analyzed based on physical phenomena of the real world, making the estimation more accurate, and have strong basics of analysis. In addition, all methods require only a single input image. This is not only practical, but also challenging in term of complexity. |
| 書誌レコードID |
|
|
収録物識別子タイプ |
NCID |
|
収録物識別子 |
AA11560603 |
| 書誌情報 |
情報処理学会論文誌コンピュータビジョンとイメージメディア（CVIM）
巻 46,
号 SIG9(CVIM11),
p. 56-59,
発行日 2005-06-15
|
| ISSN |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
1882-7810 |
| 出版者 |
|
|
言語 |
ja |
|
出版者 |
情報処理学会 |
IPSJ-TCVIM4609005 (1.9 MB)
