As a newbie in Machine Learning, I have a set of trajectories that may be of different lengths. I wish to cluster them, because some of them are actually the same pa
This is good concept and having possibility for real-time applications. In my view, one can adopt any clustering but need to select appropriate dissimilarity measure, later need to think about computational complexity. Paper (http://link.springer.com/chapter/10.1007/978-81-8489-203-1_15) used Hausdorff and suggest the technique for reducing complexity, and paper (http://www.cit.iit.bas.bg/CIT_2015/v-15-2/4-5-TCMVS%20A-edited-md-Gotovop.pdf) described the use of "Trajectory Clustering Technique Based on Multi-View Similarity"