This document is about the detection and tracking of objects in three dimensional space using the output data of a rotating laser scanner. The rotating laser scanner is a measuring device which measures the distance of points from the device and uses this measurement to determine precisely the position of the detected points. This provided data is a point cloud, which will be processed using digital video and picture processing algorithms. The first step in this process is determining the background of the captured scene, which will be thrown away because only the detection of objects is useful, the second step is using cluster builder algorithms to detect the position of unique object in every timeframe. The next step is about tracking and identifying objects in these timeframes using two different algorithms, the Kalman filter and a custom version of particle filters. To test these algorithms a software component is implemented in Java language. The result of these tests will be monitored and assessed in detail.