Segmentation and Sampling of Moving Object Trajectories Based on Representativeness

—Moving Object Databases (MOD), although ubiquitous, still call for methods that will be able to understand, search, analyze, and browse their spatiotemporal content. In this paper, we propose a method for trajectory segmentation and sampling based on the representativeness of the (sub-)trajectories in the MOD. In order to find the most representative sub-trajectories, the following methodology is proposed. First, a novel global voting algorithm is performed, based on local density and trajectory similarity information. This method is applied for each segment of the trajectory, forming a local trajectory descriptor that represents line segment representativeness. The sequence of this descriptor over a trajectory gives the voting signal of the trajectory, where high values correspond to the most representative parts. Then, a novel segmentation algorithm is applied on this signal that automatically estimates the number of partitions and the partition borders, identifying homogenous pa...

• Type: Journal
• Year: 2012
• Where: TKDE
• Authors: Costas Panagiotakis, Nikos Pelekis, Ioannis Kopanakis, Emmanuel Ramasso, Yannis Theodoridis
• Keywords: Formal Methods, Sampling Method, Sampling Techniques, Segmentation Algorithm, TKDE 2012