Advances in Stereo Vision - download pdf or read online
By J. Torreao
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The result of the modeling process is a topological graph that represents the set of rooms (nodes) and their connections (edges). Each node in this representation contains the metric description of the corresponding room model. Using this basic metric information robots do not need to maintain in parallel a metric map of the environment. Instead, this metric map can be built whenever it is necessary from the topological representation. Rooms are modeled using a variation of the Hough Transform which detects segments instead of lines.
If accepted as a real door, the robot gets out of the room to explore unknown spaces driven by the Active Modeler behavior. The room left behind is reduced to a minimal geometric parametrization and stored as a node in the graph representing the topological space. Finally, the whole process is re-initiated and new models are obtained, giving rise over time to a complete topological representation of the environment. 5. Experimental results We have carried out different experiments in real indoor environments.
Nevertheless, this is not sufficient because there are other different areas which are not sky or grass fulfilling this criterion. Therefore, we apply a classification technique based on the combination of the parametric Bayesian estimator (PB) and Parzen window (PZ) approaches. The choice of these classifiers is based on its proven effectiveness when applied individually in various fields of application, including image classification. According to (Kuncheva, 2004), if they are combined the results improve.
Advances in Stereo Vision by J. Torreao