scholarly journals Color Subspaces as Photometric Invariants

2006 ◽  
Author(s):  
T. Zickler ◽  
S.P. Mallick ◽  
D.J. Kriegman ◽  
P.N. Belhumeur
Keyword(s):  
Photometric Invariants

Photometric Invariants

2021 ◽  
pp. 970-975
Author(s):  
Todd Zickler
Keyword(s):  
Photometric Invariants

Photometric Invariants Related to Solid Shape

1980 ◽  
Vol 27 (7) ◽  
pp. 981-996 ◽  
Author(s):  
J.J. Koenderink ◽  
A.J. van Doorn
Keyword(s):  
Photometric Invariants

Feature Detection by Color Tensor-Based Photometric Invariants

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.

scholarly journals Color Subspaces as Photometric Invariants

2007 ◽  
Vol 79 (1) ◽  
pp. 13-30 ◽  
Author(s):  
Todd Zickler ◽  
Satya P. Mallick ◽  
David J. Kriegman ◽  
Peter N. Belhumeur
Keyword(s):  
Photometric Invariants
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