Clustering Moving Objects Using Segments Slopes
- Citation:
- Ossama, O., H. M. O. Mokhtar, and M. E. El-Sharkawi, "Clustering Moving Objects Using Segments Slopes", International Journal of Database Management Systems, vol. 3, issue 1, 2011.
Abstract:
Given a set of moving object trajectories, we show how to cluster them using k-means
clustering approach. Our proposed clustering algorithm is competitive with the k-means clustering
because it specifies the value of “k” based on the segment’s slope of the moving object trajectories. The
advantage of this approach is that it overcomes the known drawbacks of the k-means algorithm, namely,
the dependence on the number of clusters (k), and the dependence on the initial choice of the clusters’
centroids, and it uses segment’s slope as a heuristic to determine the different number of clusters for the
k-means algorithm. In addition, we use the standard quality measure (silhouette coefficient) in order to
measure the efficiency of our proposed approach. Finally, we present experimental results on both real
and synthetic data that show the performance and accuracy of our proposed technique.