DETECTING AND TRACKING MOVING OBJECTS USING STATISTICAL ADAPTIVE THRESHOLDING APPROACH WITH SOM & GMA TRACKING

One of the biggest obstacles is finding and tracking moving items in an urban area. This paper offers a standard way for detecting objects in their dynamics so that every object in the scene can be detected in order to handle the challenge. This method uses a static obstacle map and statistical adaptive thresholding. On the basis of their determined threshold and likelihood, those objects were then divided into static and dynamic categories. It is therefore possible to track the resulting dynamic objects using a geometric model-free approach (GMA). When compared to the previous methods, which either used a static obstacle map or statistical adaptive thresholding, the accuracy has greatly increased.