Color Subspaces as Photometric Invariants

2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) ◽

10.1109/cvpr.2006.77 ◽

2006 ◽

Cited By ~ 3

Author(s):

T. Zickler ◽

S.P. Mallick ◽

D.J. Kriegman ◽

P.N. Belhumeur

Keyword(s):

Photometric Invariants

A class of photometric invariants: separating material from shape and illumination

Proceedings Ninth IEEE International Conference on Computer Vision ◽

10.1109/iccv.2003.1238652 ◽

2003 ◽

Cited By ~ 24

Author(s):

Narasimhan ◽

Visvanathan Ramesh ◽

Nayar

Keyword(s):

Photometric Invariants

10.1007/978-3-030-63416-2_544 ◽

2021 ◽

pp. 970-975

Author(s):

Todd Zickler

Keyword(s):

Photometric Invariants

On identification of singular points using photometric invariants for global shape from shading problem

Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170) ◽

10.1109/icpr.1998.712075 ◽

2002 ◽

Author(s):

T. Okatani ◽

K. Deguchi

Keyword(s):

Shape From Shading ◽

Singular Points ◽

Global Shape ◽

Photometric Invariants

Linear spectral unmixing of sets of mixed pixels using photometric invariants

IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) ◽

10.1109/igarss.2000.860362 ◽

2002 ◽

Author(s):

M. Faraklioti ◽

M. Petrou

Keyword(s):

Spectral Unmixing ◽

Mixed Pixels ◽

Linear Spectral Unmixing ◽

Photometric Invariants

Photometric Invariants Related to Solid Shape

Optica Acta International Journal of Optics ◽

10.1080/713820338 ◽

1980 ◽

Vol 27 (7) ◽

pp. 981-996 ◽

Cited By ~ 161

Author(s):

J.J. Koenderink ◽

A.J. van Doorn

Keyword(s):

Photometric Invariants

Using Photometric Invariants for 3D Object Recognition

Computer Vision and Image Understanding ◽

10.1006/cviu.1997.0603 ◽

1998 ◽

Vol 71 (1) ◽

pp. 74-93 ◽

Cited By ~ 6

Author(s):

Kenji Nagao ◽

W.Eric.L. Grimson

Keyword(s):

Object Recognition ◽

3D Object Recognition ◽

3D Object ◽

Photometric Invariants

Feature Detection by Color Tensor-Based Photometric Invariants

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.341-342.540 ◽

2011 ◽

Vol 341-342 ◽

pp. 540-545

Author(s):

Xing Sheng Yuan ◽

Zheng Zhi Wang

Keyword(s):

Computer Vision ◽

Real World ◽

Vision Research ◽

Feature Detection ◽

Invariant Features ◽

Photometric Invariance ◽

Invariance Theory ◽

Photometric Invariants

Although the majority of images are recorded in color format nowadays, computer vision research is still mostly restricted to luminance-based feature detection. In this paper, we combine the features based on the color tensor with photometric invariant derivatives to arrive at photometric invariant features. The combination of the photometric invariance theory and tensor based features allows for detection of a variety of features such as photometric invariant edges, corners. Experiments show that the proposed features are robust to scene incidental events and perform well in real-world scene.