1. Gesture Recognition Inside a Car Using IR-UWB Radar
Professor Sung Ho Cho
Communication & Signal Processing Lab Hanyang University

2. OUTLINE
Problem Statement
System Block Diagram
Features Extraction
Gestures Training
Gestures Classification
Results & Discussion

3. Current Solutions for Gesture Recognition
Problem Statement
Current Solutions for Gesture Recognition
Vision based gesture recognition Glove Based Solution
Main Issues
Privacy Issues (Camera Based)
Environmental factors that cause vision interference like light, fog, and smoke
Inconvenience (Glove based)
IR UWB Based Gesture Recognition
No privacy Issue
Higher range resolution, low power consumption
Performance not effected by darkness

4. Novelda NVA6201 Specifications
Experimental Setup
Novelda NVA6201 Specifications
Parameter
Value
PRF
100 MHz
Centre Frequency
6.8 GHz
Bandwidth
2.3 GHz
Output Power
-53 dBm/MHz

5. Process Block Diagram

6. Signal Pre-Processing
Clutter Removal
Averaging of the signal & Separation of human body from human hand
Detect the peaks above the threshold
Chose the Nearest peak to Radar

7. Gestures Defined on basis of features
The Variance of Displacement of nearest point above threshold
Variance of magnitude
Surface Area of the hand
Gesture Notation
Description G1
When hand moves back and forth while palm is open G2
When hand palm is open and fixed G3
Hand fingers are closed and stationary G4
Similar to G2 but palm facing radar sidewise G5
The fingers are opened and closed continuously while hand position is fixed G6
The palm is facing the ground and hand is stationary

8. Gesture Training
No. of Gestures

9. Extracted Feature’s Mean Values

10. Decision Tree

11. Results Gesture Result of Recognition Number of Trial
Number of Correct
Accuracy G1
150
100% G2
131
87.33% G3
125
83.33% G4
134
89.34% G5 G6
127
84.67%

12. Discussion Achievements Future Work
Developed and performed the algorithm in Lab environment
Tested it in a Stationary Car
Future Work
Gesture Recognition inside a moving Car
Motion Compensation of Radar
Motion Compensation of Body

13. Thank You