Ship Trajectory Clustering Based on Trajectory Resampling and Enhanced BIRCH Algorithm

Shape-based Trajectory Clustering

Automatic trajectory classification has countless applications, ranging from the natural sciences, such as zoology and meteorology, to urban planning and sports analysis, and has generated great interest and investigation. The purpose of this work is to propose and test new methods for trajectory clustering, based on shape, rather than spatial position, as is the case with previous methods. The...

Enhanced User Authentication through Trajectory Clustering

* Hazarath Munaga alias MHM Krishna Prasad Abstract— Password authentication is the most commonly used technique to authenticate the user validity. However, due to its simplicity, it is vulnerable to pseudo attacks. It can be enhanced using various biometric techniques such as thumb impression, finger movement, eye movement etc. In this paper, we concentrate on the most economic technique, base...

Sampling-based Sub-Trajectory Clustering

Density Based k-Nearest Neighbors Clustering Algorithm for Trajectory Data

With widespread availability of low cost GPS, cellular phones, satellite imagery, robotics, Web traffic monitoring devices, it is becoming possible to record and store data about the movement of people and objects at a large amount. While these data hide important knowledge for the enhancement of location and mobility oriented infrastructures and services, by themselves, they demand the necessa...

The Ship Movement Trajectory Prediction Algorithm Using Navigational Data Fusion

It is essential for the marine navigator conducting maneuvers of his ship at sea to know future positions of himself and target ships in a specific time span to effectively solve collision situations. This article presents an algorithm of ship movement trajectory prediction, which, through data fusion, takes into account measurements of the ship's current position from a number of doubled auton...