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Event-Based Sensing (EBS)—also known as neuromorphic imaging—is an emerging sensor technology inspired by the human visual system. Instead of capturing full image frames at a fixed rate, EBS pixels operate independently, asynchronously reporting changes in brightness as discrete “events” with microsecond precision.

This approach provides several key advantages for GEOINT applications:

Ultra-high temporal resolution for capturing fast-moving or fast-changing scenes with minimal motion blur and reduced latency.
High dynamic range, allowing meaningful data collection in conditions where conventional sensors saturate.
Power efficiency, since only brightness changes are reported, producing sparse data streams suitable for edge computing.

Attendees will explore the latest visible and infrared EBS cameras, simulation tools, and processing workflows. Using open-source EBS simulators, participants will learn how to synthesize event streams from conventional video and apply AI/ML-based methods for processing asynchronous data. The session will highlight two GEOINT applications in detail:

Tracking dim, fast-moving, unresolved targets from satellites, supporting missile tracking and guidance missions.
Vehicle re-identification by linking EBS satellite data with GMTI and conventional imagery.

Learning Outcomes

Understand how EBS differs from traditional frame-based sensors in temporal resolution, dynamic range, and power consumption
Identify current commercial EBS camera technologies in visible and infrared bands
Use simulation and AI/ML tools to generate and process event data streams
Explore real-world GEOINT applications for EBS, including fast object tracking and vehicle re-identification

Prerequisites

No formal prerequisites. This session is ideal for engineers, optical scientists, analysts, and decision-makers with a general understanding of imaging, computer vision, or AI/ML concepts.

GEOINT 2026

Event-Based Sensing: What Is It and How Is It Relevant to GEOINT?

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