Leveraging the Properties of mmWave Signals for 3D Finger Motion Tracking for Interactive IoT Applications

Keyphrases

• Forearm 100%
• Mm-wave Frequencies 100%
• IoT Applications 100%
• Finger Tracking 100%
• Finger Movement 60%
• Occlusion 40%
• Non-line-of-sight (NLoS) 40%
• Low Energy 20%
• Latency 20%
• Performance Evaluation 20%
• Privacy Concerns 20%
• Location Error 20%
• Smartphone 20%
• Natural Variation 20%
• Vision-based 20%
• Vibration Pattern 20%
• Specular Reflection 20%
• Encoder-decoder 20%
• Clothing 20%
• Architecture-centric 20%
• Hand Position 20%
• Multipath 20%
• Privacy-preserving 20%
• Energy Overhead 20%
• Millimeter Wave 20%
• Pattern Diversity 20%
• Paper Design 20%
• Anatomical Constraints 20%
• Accurate Tracking 20%
• U-Net 20%
• Next Generation Wireless Networks 20%
• Gesture Classification 20%
• Systematic Performance 20%
• Hardware Noise 20%
• Poor Lighting 20%
• MmWave Sensing 20%

Computer Science

• IoT Application 100%
• Privacy Concern 33%
• Performance Evaluation 33%
• Search Space 33%
• Privacy Preserving 33%
• Critical Component 33%
• Wireless Network 33%
• Location Error 33%
• Specular Reflection 33%

Engineering

• Location Error 33%
• Specular Reflection 33%
• Search Space 33%
• Natural Variation 33%