ST-SiameseNet: Spatio-Temporal Siamese Networks for Human Mobility Signature Identification

Abstract

Given the historical movement trajectories of a set of individual human agents (e.g., pedestrians, taxi drivers) and a set of new trajectories claimed to be generated by a specific agent, the Human Mobility Signature Identification (HuMID) problem aims at validating if the incoming trajectories were indeed generated by the claimed agent. This problem is important in many real-world applications such as driver verification in ride-sharing services, risk analysis for auto insurance companies, and criminal identification.

Year of Publication
2020
Conference Name
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
Date Published
08