Clustering

Background

This is an important feature for big clients, like RMS, that have Face Recognition feature and it’s getting harder and harder to assign hundreds of profiles.

Concept Description

This is a Clustering algorithm for unassigned drivers’ profiles that simplifies the assignment process. Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). In our case, it’s grouping a set of pictures that are similar and may or may not belong to a driver.

Technical Development

The easier part is that ‘these profiles that might be from the same driver’ will group similar profiles and simplify the assignment, much better than select profiles from an infinite list. Every single profile needs to be assigned to the related driver, otherwise the system will not work properly at all. It is very important that the system learns its drivers, so the recognition can be accurate. Those clusters are grouped per each location Each cluster will have a set of profiles, that may or may not be from the same driver. You can easily assign them to one of your drivers