Tomographic Proximity Imaging Using Conductive Sheet for Object Tracking.

Area of Science:

• Electrical Engineering
• Sensor Technology
• Computational Imaging

Background:

• Traditional proximity sensors often lack detailed spatial information or are costly.
• Developing cost-effective sensors for precise proximity detection remains a challenge.
• Tomographic methods offer potential for reconstructing spatial information from limited measurements.

Purpose of the Study:

• To propose and validate a novel proximity imaging sensor utilizing a tomographic approach.
• To develop a theoretical model for converting capacitance density to electric potential for proximity sensing.
• To demonstrate the sensor's capability in object localization and real-time hand tracking.

Main Methods:

• A low-cost conductive sheet was employed as the sensing element.
• A theoretical model was developed to solve the capacitance density problem via tomography.
• An inverse problem was formulated and solved to image capacitance density changes.
• A prototype sensor was constructed and evaluated for localization accuracy and hand-tracking performance.

Main Results:

• The proximity sensor successfully transformed physical proximity into measurable electric potential.
• The prototype achieved horizontal localization errors between 10.0% and 15.8% at varying heights.
• Hand-tracking demonstrated a position difference of 33.8–46.7 mm compared to a depth camera at 30 frames per second.

Conclusions:

• The proposed tomographic proximity imaging sensor is a viable, low-cost solution for spatial awareness.
• The developed theoretical model and inverse problem-solving approach enable effective proximity imaging.
• The system shows promise for applications requiring real-time, accurate proximity detection and tracking.