AI-Powered Multi-Camera Tracking

Speed development of the next wave of vision AI that measures and helps manage infrastructure and operations over large spaces.


Computer Vision / Video Analytics


Smart Cities / Spaces
Retail/Consumer packaged goods
Healthcare and Life Science

Business Goal

Return on Investment
Risk Mitigation


NVIDIA Metropolis
NVIDIA Omniverse
NVIDIA AI Enterprise

What Is Multi-Camera Tracking?

Imagine a world where factories run automatically with safety and efficiency, retail spaces are optimized for the shopper experience, and public spaces like hospitals, airports, and highways are safer and more streamlined. These spaces are too large for a single camera to cover, so they’re typically monitored by hundreds of cameras. Following objects and measuring activity accurately across cameras and space is called multi-camera tracking, letting you effectively monitor and manage your spaces.

AI-Powered Multi-Camera Application Development

NVIDIA's customizable multi-camera tracking workflow gives you a starting point to get your development in gear without having to start from scratch and eliminates months of development time. The workflow also provides a validated path to production.

The solution includes state-of-the-art AI models pretrained on real and synthetic datasets that you can customize for your use case. It covers the entire lifecycle—from simulation to analytics—and integrates NVIDIA's cutting-edge tools, including Isaac SIM™, Omniverse™, TAO, and DeepStream. This workflow is packed with real-time video streaming modules and is built on a scalable, cloud-native microservices architecture. No extra cost, just infrastructure and tool licenses. Plus, you get expert support and the latest product updates with NVIDIA AI Enterprise to accelerate your vision AI project.

How Can You Use Multi-Camera Tracking?

Manufacturing and warehouse automation: Improve your shop floor operations by optimizing routes for autonomous robots, equipment, and workers. AI-powered analytics help identify congestion, bottlenecks, and risks, allowing for data-driven decisions that enhance productivity and worker safety. 

Retail store layout optimization: By analyzing customer navigation throughout your store, you can reconfigure aisles and product placement to maximize sales and revenue. Multi-camera tracking helps identify bottlenecks, track customer behavior, and simulate layout scenarios to predict impact on sales and customer experience. 

In-hospital patient care: Access continuous monitoring of patients in hospitals for an added layer of safety and security. The solution enables real-time alerts and notifications, ensuring prompt attention and care when it’s needed.

Fusing Real-Time AI With Digital Twins

In this demo, a digital twin of a warehouse built using the NVIDIA Omniverse platform operates as a simulation environment for dozens of digital workers and multiple autonomous robots. The multi-camera tracking workflow enabled the creation of a centralized map of the entire warehouse with 100 simulated cameras, providing real-time  awareness of the physical space.

End-to-End Workflow for Multi-Camera Tracking

This workflow includes the entire development pipeline—from data generation to model training to application development—to help developers build complex vision AI applications for large spaces.

NVIDIA software tools enable an end-to-end workflow to build these applications faster:


  • Create 3D digital twins of real-world environments using NVIDIA Omniverse.

  • Using NVIDIA Omniverse—a platform for building and operating metaverse applications—developers can construct 3D digital twins of real-world spaces, position virtual cameras to capture diverse synthetic data, generate ground-truth annotations for training perception models, and validate end-to-end applications prior to real-world deployment.


  • NVIDIA Isaac Sim for synthetic data generation to optimize training.

  • Using Omni.Replicator.Agent (ORA) within Isaac Sim simplifies agent simulation, including people and autonomous moving robots, streamlining the generation of synthetic data from scenes.


  • NVIDIA TAO toolkit for streamlined model development with real and synthetic data.

  • The NVIDIA TAO Toolkit simplifies model training and optimization for tasks such as people detection and re-identification. Developers can fine-tune pretrained models with synthetic and real data and optimize for better inference performance through quantization and pruning.


  • Use Metropolis microservices as flexible building blocks for AI application development.

  • NVIDIA Metropolis microservices provide developers with a comprehensive suite of cloud-native building blocks to accelerate AI development. The microservices include media services for camera discovery and management, perception services for people detection, tracking, and re-identification, spatio-temporal services for real-time insights across multiple cameras, and analytics services.


  • Cloud-native design for scalable deployment from edge to cloud.

  • Containerize your applications easily with Docker, Kubernetes, and GPU Operators to deploy cloud-native solutions on NVIDIA Jetson™, x86, and dGPU.


Jumpstart development of multi-camera vision AI applications with NVIDIA's accelerated 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.

Accelerate the development of your multi-camera tracking AI application.