Retail Footfall Camera Kit v35: Dual Camera Stereo Depth with Raspberry Pi 5

Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.

Retailers track customer movement with overhead cameras, but single-sensor systems can't distinguish depth or crowd flow accurately. This kit lets you build a dual-camera rig that computes stereo disparity maps, reconstructing 3D depth from two Pi Camera Module 3 streams on a Raspberry Pi 5—the same underlying technique used in modern retail analytics platforms.

What You'll Build

By assembling this kit, you create a standalone stereo depth sensor that outputs real-time disparity maps. The calibrated dual camera setup generates pixel-level depth information, which you can use to count people entering a store, measure queue occupancy, or map high-traffic zones. It's a complete edge AI device that turns a simple retail space into a data-rich environment.

What You'll Learn

• Calibrate a stereo camera pair using OpenCV on Raspberry Pi 5
• Compute disparity maps and 3D depth from dual 12MP video streams
• Store high-throughput image data on NVMe SSD for real-time processing
• Interpret depth data for retail footfall analytics and crowd density estimation

Kit Contents