Papers
2
Total Citations
17
H-Index
1
About
Wentao Pan is a researcher whose work bridges biomechanics, machine learning, and digital security. His most influential contribution, "Human Walking Pattern Recognition Based on KPCA and SVM with Ground Reflex Pressure Signal" (2013, 16 citations), pioneered the use of ground reflex pressure signals from sensing shoes for gait analysis. By applying kernel principal component analysis (KPCA) for dimensionality reduction and support vector machines (SVM) for classification, Pan developed robust algorithms for identifying human walking patterns—a foundational advance for assistive robotics, rehabilitation, and biometric authentication. More recently, Pan has ventured into the cutting-edge domain of 4D Gaussian Splatting (4D-GS) for dynamic scene reconstruction. His 2025 work, "Hide-in-Motion: Embedding Steganographic Copyright Information into 4D Gaussian Splatting Assets," addresses a critical security challenge as these techniques gain traction in robotics and computer vision. By embedding imperceptible steganographic watermarks into 4D-GS assets, Pan provides a novel method for protecting intellectual property in dynamic visual data. Though early in its citation trajectory, this work signals his forward-looking focus on trustworthiness in emerging 3D/4D representations. Pan’s career exemplifies a rare versatility—from sensor-based biomechanics to steganographic security—demonstrating a commitment to solving real-world problems across diverse technological frontiers.
Research Focus
Key Achievements
Top Papers
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