Proximity-Based Sensor Fusion of Depth Cameras and Isotropic Rad-Detectors

Abstract

Finding and tracking radioactive sources have numerous security applications in civilian energy installations, military facilities, and ports of entry. The price of radiological sensors varies proportionally to size and imaging characteristics such as angular resolution, and the cheapest devices are nearly isotropic–i.e., they integrate radiation from a sphere of directions centered at the sensor. While many radiation sensors have high aspect ratios or odd shapes, the sensors used here are right cylinders, with a near identical directional efficiency such that for analysis purposes, other aspects, such as counting statistics, would make nonisotropy of the sensor negligible. In this article, we propose a simple and robust way to integrate measurements from both isotropic radiological sensors and depth sensors, whose reliability and resolution benefit from recent advances in computer vision and imaging. Our key idea is to convert all sensor measurements into proximity signals based on radial distance variations over time. Based on this sensor fusion model, we show that for moving radiological sources even a simple Kalman filter can trade-off the complementary strength of high-resolution depth sensors and isotropic radiological sensors. We show novel results with a LIDAR sensor and a thermal stereo pair, and demonstrate applications such as tracking and rendering non-line-of-sight imagery behind obstacles and detecting multiple radiological sources in the same scene.