Computer Vision at Scale: Multi-Camera Tracking, Calibration, and Event Detection for Checkout-Free Retail

Large-scale multi-camera systems are central to real-world computer vision applications, yet their design is shaped as much by infrastructure constraints as by algorithmic advances. This tutorial presents a unified perspective on multi-camera vision through the lens of checkout-free retail, focusing on three core components: automatic camera calibration, real-time multi-object tracking, and structured event detection. It examines how challenges such as asynchrony, partial observability, hardware failures, and edge deployment constraints influence system design and performance. The tutorial further highlights generalizable principles for building reliable, scalable vision systems, bridging the gap between academic methods and real-world deployment.