Time-of-flight sensor depth enhancement for automotive exhaust gas

The Time-of-Flight (ToF) sensor has been envisioned as a candidate of next generation sensors for intelligent vehicles. One of the problems in automotive environment is that the sensor outputs wrong values if exhaust gas exists in the scene. In this paper, we provide two new contributions to the signal processing aspects of the ToF sensor for automotive use. First, we present the sensor characteristics and models for exhaust gas to cope with them. Second, we develop a depth enhancement algorithm to reject the influence of exhaust gas from multiple images. Experimental results demonstrate the effectiveness of the depth enhancement algorithm for both static data (including ground truth) and on-vehicle data acquired by the sensor mounted on a car.