Directional gradients integration image for illumination insensitive face representation
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Summary
Experiments on the Yale B, the extended Yale B and the CMU PIE face databases show that the proposed method provides better results than some state-of-the-art methods, showing its effectiveness for illumination normalization.
- Type
- article
- Published
- 2018-05-12
- Cited by
- 0
- References
- 30
- OpenAlex
- https://openalex.org/W2801840334
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:21657704
Keywords
Artificial intelligence, Computer science, Computer vision, Normalization (sociology), Pattern recognition (psychology)
References
- What Is the Set of Images of an Object Under All Possible Illumination Conditions?
- Face recognition by elastic bunch graph matching
- Face recognition: A literature survey
- The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations
- Illumination Invariant Face Recognition: A Survey
- Face recognition under variable lighting using harmonic image exemplars
- Integral Normalized Gradient Image A Novel Illumination Insensitive Representation
- A bilinear illumination model for robust face recognition
- Normalization of Face Illumination Based on Large-and Small-Scale Features
- Properties and performance of a center/surround retinex
- From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
- Face recognition under varying lighting conditions using self quotient image
- Acquiring linear subspaces for face recognition under variable lighting
- Online recognition of freely handwritten Japanese characters using directional feature densities
- Nine points of light: acquiring subspaces for face recognition under variable lighting
- Illumination-insensitive face recognition using symmetric shape-from-shading
- Lambertian reflectance and linear subspaces
- Face Recognition: The Problem of Compensating for Changes in Illumination Direction
- Total variation models for variable lighting face recognition
- Illumination cones for recognition under variable lighting: faces
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