Robust heterogeneous discriminative analysis for face recognition with single sample per person

Keyphrases

• Face Recognition 100%
• Discriminant Analysis 100%
• Single Sample per Person 100%
• Patch-based 40%
• Fisher-like Criterion 40%
• Facial Variation 40%
• Distance Metric 40%
• Benchmark Dataset 20%
• Image Patch 20%
• Challenging Problems 20%
• Discriminative Representation 20%
• Inter-patch Distance 20%
• Majority Voting 20%
• Manifold Embedding 20%
• Fusion Strategy 20%
• Manifold Distance 20%
• Feature Extraction 20%
• Graph-based 20%
• Feature Identification 20%

Computer Science

• Face Recognition 100%
• Distance Metric 40%
• Experimental Result 20%
• Majority Voting 20%
• Feature Extraction 20%