Pedestrian quantity estimation with trajectory patterns
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part II
| Hi-index | 0.00 |
We introduce s-kNN, a nearest neighbor based spatial data mining algorithm. It belongs to the class of vector-geometry based algorithms that reason on complex spatial objects instead of point measurements. In contrast to most methods in this class, it does on the fly spatial computations that cannot be replaced by a pre-processing step without sacrificing efficiency. The key is a partial evaluation scheme for efficient computations. The algorithm is fully integrated into an object-relational spatial database. It is the basis for traffic frequency predictions (vehicles and pedestrians) for all German cities larger than 50,000 inhabitants and is the basis for pricing of posters in Germany.