Video-Based Palm-Vein Authentication under Challenging Conditions
Palm-vein biometrics are increasingly used for secure, contactless authentication. Yet real-world deployment exposes them to surface noise (sweat, dirt), illumination and motion variation, and temperature-driven changes in vascular visibility, which remain underexplored for lack of data captured under such conditions. To study these effects, we introduce the Columbia University Palm-vein (CUP) dataset, to our knowledge the first public video-based palm-vein dataset. CUP records every palm under four surface conditions (a clean baseline, warm, wet, and dirty) and pairs each subject with physiol
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- FuzzyOverlapping authors or contributors · 62%modular/modular →
“Shared author/contributor keys: liu”
- FuzzyOverlapping authors or contributors · 62%sgl-project/sglang →
“Shared author/contributor keys: zhou”
- FuzzySimilar title/name (fuzzy) · 59%Developer-Y/cs-video-courses →
“Fuzzy title match (0.73): “Video-Based Palm-Vein Authentication under Challenging Condi” ≈ “Developer-Y/cs-video-courses””
- LinkedLinked via arxiv author · 85%Xiaofeng Yan →
“Video-Based Palm-Vein Authentication under Challenging Conditions”
- LinkedLinked via arxiv author · 85%Kechen Liu →
“Video-Based Palm-Vein Authentication under Challenging Conditions”
- LinkedLinked via arxiv author · 85%Abhilash Venkatesh →
“Video-Based Palm-Vein Authentication under Challenging Conditions”
- LinkedLinked via arxiv author · 85%Cathy Zhang →
“Video-Based Palm-Vein Authentication under Challenging Conditions”
- LinkedLinked via arxiv author · 85%Xia Zhou →
“Video-Based Palm-Vein Authentication under Challenging Conditions”