Developers building video analytics applications across large spaces must track the same object as it moves between camera views. Single-camera 2D tracking lacks reliable depth information and typically loses track of the object when it leaves the frame, limiting applications such as warehouse safety, retail analytics, and smart-building monitoring. Current 3D tracking methods require manual camera calibration and complicated calculations.
NVIDIA DeepStream 9.1 addresses this challenge with AutoMagicCalib (AMC) and Multi-View 3D Tracking (MV3DT). AMC and MV3DT fuses detections from multiple auto-calibrated cameras into a shared 3D coordinate system and maintains a consistent object ID across views.
This post will cover the details of MV3DT and AMC, and how to get started with DeepStream 9.1, a major leap forward in simplifying and accelerating vision AI pipeline development.
With a strong focus on modularity, automation, and edge performance, DeepStream 9.1 introduces a set of powerful agentic skills that help developers move from concept to deployment faster and with greater accuracy.
What’s new with DeepStream 9.1:
