Unlock Advanced Human Detection with Multimodal Remote Sensing & Thermal Modeling in MuSES

On-Demand Webinar

Multimodal human detection depends on training data that captures real-world variation. This includes pose, clothing, environment, and sensor perspective. However, that kind of diversity is difficult to obtain from measured sources alone.

This webinar explored the integration of multimodal remote sensing data and human thermal modeling within MuSES. Specifically, MuSES is the premier simulation environment for realistic battlefield and security scenarios in the infrared (IR) spectrum.

We demonstrated how synthetic imagery generated across the LWIR, MWIR, and SWIR bands can train and test AI/ML detection algorithms. As a result, detection performance improves significantly over single-band approaches. In addition, we showed how continued improvements in human thermal modeling fidelity translate directly into more realistic IR signatures for training data. This includes advances in clothing, hair, and equipment representation.

Key Takeaways

• Multimodal Dataset Generation: How MuSES and CoTherm generate synthetic LWIR, MWIR, and SWIR imagery datasets for human detection training.
• Advanced Human Thermal Modeling: Improvements in geometry, hair, and clothing fidelity that increase the realism of human IR signatures.
• Automated Target Detection: Applying YOLO11 to synthetic and measured imagery to evaluate detection and recognition performance.
• Cross-Waveband Performance Insights: How training in one sensor waveband translates to testing in another, and what that means for real-world deployment.
• Scene and Terrain Automation: Tools for building diverse, realistic backgrounds to support large-scale synthetic dataset generation.

Who Should Watch

• Defense Engineers and Researchers working on ISTAR (intelligence, surveillance, target acquisition, and reconnaissance) applications.
• Data Scientists and Image Analysts training AI/ML models for human detection and recognition.
• Program Managers focused on soldier vulnerability, mission planning, and automated security applications.

Presenters

Scott Gibbs

Senior Thermal and EO/IR Analyst

Scott Gibbs is a Senior Engineer at ThermoAnalytics, where he leads the Electro-Optical/Infrared (EO/IR) Engineering Team. He specializes in thermal and EO/IR signature prediction, field test validation of military vehicles, and synthetic scene generation for AI/ML training using MuSES. His work includes validating the Small Diameter Bomb II (SDB-II) missile seeker program and contributing to the development of the first female physiology model used in ThermoAnalytics’ human thermal simulation software. Mr. Gibbs holds a B.S. in Mechanical Engineering from Michigan State University.

Audrey Levanen

Thermal/CFD Engineer

Audrey Levanen is a Thermal/CFD Engineer at ThermoAnalytics, Inc., where she supports defense-focused thermal and infrared modeling, synthetic data generation for AI/ML applications, and human comfort simulation projects. She has developed custom Python tools for automating image annotation and analyzing thermal comfort results, helping streamline workflows for both simulation and data science teams. Audrey joined ThermoAnalytics full-time in 2023 after interning with the company and earning her B.S. in Mechanical Engineering from Michigan Technological University.

Watch the Webinar