Announcing the Official Release of the Metropolis Multi-Camera Tracking AI Workflow
Published:
I am thrilled to share that our pioneering work, the Metropolis Multi-Camera Tracking AI Workflow, was prominently featured in NVIDIA GTC’24 Keynote by Jensen Huang. As the Tech Lead of this groundbreaking project, it is an honor to announce that our innovative solution is now officially available.
Our AI-powered multi-camera tracking system is designed to accelerate the development of vision AI applications, providing a comprehensive solution for measuring and managing infrastructure and operations across large spaces.
Imagine a world where factories operate automatically with maximum safety and efficiency, retail spaces are optimized for a superior shopper experience, and public areas like hospitals, airports, and highways are safer and more streamlined. Multi-camera tracking allows for accurate object tracking and activity measurement across multiple cameras and spaces, enabling effective monitoring and management.
NVIDIA’s customizable multi-camera tracking workflow offers a validated path to production, eliminating months of development time. The solution includes state-of-the-art AI models pretrained on real and synthetic datasets, customizable for various use cases. The workflow spans from simulation to analytics and integrates NVIDIA’s cutting-edge tools, including Isaac SIM™, Omniverse™, TAO, and DeepStream. It features real-time video streaming modules and is built on a scalable, cloud-native microservices architecture. With expert support and the latest product updates through NVIDIA AI Enterprise, this workflow accelerates vision AI projects without additional costs, apart from infrastructure and tool licenses.
Applications of multi-camera tracking include enhancing manufacturing and warehouse operations by optimizing routes for autonomous robots, equipment, and workers. It also improves retail store layouts by analyzing customer navigation to maximize sales and revenue, and enhances in-hospital patient care by providing continuous monitoring for safety and security.
Our workflow includes the entire development pipeline—from data generation to model training to application development—helping developers build complex vision AI applications for large spaces. Key components include creating 3D digital twins of real-world environments using NVIDIA Omniverse, simplifying agent simulation with NVIDIA Isaac Sim, streamlining model training with NVIDIA TAO Toolkit, and using NVIDIA Metropolis microservices for modular, cloud-native application building blocks.
Jumpstart the development of multi-camera vision AI applications with NVIDIA’s end-to-end workflow, from Omniverse simulation for synthetic data generation to TAO for streamlined model development to Metropolis microservices for modular, cloud-native application building blocks.
Join us in this exciting journey towards transforming how we monitor and manage large spaces with cutting-edge AI technology.
