Over the years imaging laser radar systems have been developed for military and civilian applications. Among the applications we note collection of 3D data for terrain modeling and object recognition. One part of the object recognition process is to estimate the size and orientation of the object. This paper concerns a vehicle size and orientation estimation process based on scanning laser radar data. Methods for estimation of the length and width of vehicles are proposed. The work is based on the assumption that from a top view most vehicles' edges are approximately of rectangular shape. Thus, we have a rectangle fitting problem. The first step in the process is sorting of data into lists containing object data and data from the ground closest to the object. Then a rectangle with minimal area is estimated based on object data only. We propose an algorithm for estimation of the minimum rectangle area containing the convex hull of the object data. From the rectangle estimate, estimates of the length and width of the object can be retrieved. The first rectangle estimate is then improved using least squares methods based on both object and ground data. Both linear and nonlinear least squares methods are described. These improved estimates of the length and width are less biased compared to the initial estimates. The methods are applied to both simulated and real laser radar data. The use of the minimum rectangle estimator to retrieve initial parameters for fitting of more complex shapes is discussed.
Vehicle size and orientation estimation using geometric fitting
2001
12 Seiten, 18 Quellen
Aufsatz (Konferenz)
Englisch
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