Dynamic Crowd Insights: Spatial Mapping for Retail Environment Optimization

Transforming Retail Video Feeds into Customer Engagement Visualizations

Keywords: Homography Transform, Crowd Analysis, Store Layout Optimization, Computer Vision

Brief Description

This project extends my camera-feed-processing pipeline (github repo) to develop a video analysis system for customer behavior insights in retail environments. The system processes feeds from multiple cameras distributed across a retail outlet, generating comprehensive customer engagement reports overlaid on dynamic floor plans.

Homography Transform

The idea is to employ homography transforms to map detected personnel coordinates from camera views to actual floor plan positions. This process can be represented mathematically as:

\[\begin{bmatrix} x' \\ y' \\ w \end{bmatrix} = \begin{bmatrix} h_{11} & h_{12} & h_{13} \\ h_{21} & h_{22} & h_{23} \\ h_{31} & h_{32} & h_{33} \end{bmatrix} \begin{bmatrix} x \\ y \\ 1 \end{bmatrix}\]

Where \((x, y)\) are the coordinates in the camera view, and \((x'/w, y'/w)\) are the corresponding coordinates on the floor plan.

Key Technologies and Architecture
  • Computer Vision: YOLOv8 for identifying and tracking customers
  • Spatial Mapping: Homography transforms for positioning on floor plans
  • Data Visualization: Dynamic heatmaps for spatial analysis of customer movements
  • Distributed Processing: Utilizes asynchronous frame-ingestion and processing pipeline
  • Analytics Dashboard: Near real-time visualization of customer distribution across zones
underlying system design - discussed on github; this post is about a specific processing service
Applications and Future Development
  • Manpower Allocation: Optimizing staff placement based on customer density
  • Product Placement: Informing strategic positioning of products and promotional materials
  • Customer Flow Analysis: Understanding movement patterns for store layout optimization

Future development aims to incorporate demographic analysis from the detections, providing more nuanced and actionable insights for retail strategy.

Illustration