Semantic Hierarchy Fusion of Image Sensors and Supersonic wave Sensors

Recently, a lot of image sensors are employed for the purpose of incident detection, because image sensors can provide much more rich information than spot sensors such as supersonic wave sensors. However, it is quite difficult to achieve high accuracy by image recognition methods because of their instability against environmental changes. On the other hand, for example, supersonic wave sensors have advantages on robustness against environmental changes, and it requires less CPU performance than image sensors. Therefore, future event detection system should collaborate different sensors in order to realize a totally efficient surveillance system. In this paper, we developed algorithms for incident detection by sensor fusion technique among the two different sensors. The algorithm was evaluated by using 3 month data of images and supersonic waves on expressway in Tokyo containing about 20 incidents. And the algorithm was then proved to be more accurate than the algorithm using a single video image which we previously developed for incident detection.