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Summarizing and Searching Video: Patterns-of-Life Analysis

This poster reports on experiments to use simulation to explore the possibilities of patterns-of-life analysis with perfect data.

Software Engineering Institute


Over the past five years, image recognition has improved dramatically thanks to new deep-learning architectures. While much progress has been made, real-time tracking is still an emerging technology. Tracks can be lost, or registration errors can occur. In addition, it is very difficult to obtain ground truth for this type of data. For these reasons, we have chosen to use simulation to generate synthetic patterns to explore the possibilities of PoL analysis with perfect data. We use the SUMO traffic simulator and have explored both classification and anomaly detection tasks using this data.