VideoSift: Analysis of Video for Retail

Client Company

Shopping Malls in Russia and Algeria

Solution Description

A solution that analyzes IP-camera videos from shopping malls in real-time to recognize and count every visitor in view; collect statistics on the visitors for further analysis and reporting, and build visits heat map.

VideoSift addresses the clients’ daily needs by providing:

  1. Visualization of visitors’ movements across the mall

  2. Statistics on visitors entry hours, identification of peak hours and conversions into buyers at any moment

  3. Statistics on all clients for any timeframe for making the comparative study to achieve the best traffic monetization

Technology background

The system is based on Neural Networks and Machine Learning, the main functions include

  • Video Processing

    based on an open-cv library (a classical pipeline for video processing)
  • Object Detection

    a fast open-source solution built on http://dlib.net/
  • Person Recognition

    use of machine-learning models based on TensorFlow framework
  • Unique Counting

    proprietary hash function algorithm for further advanced identification
  • Gender and Age Identification

    based on neural networks

Results and Current Status

The application has proven its reliability for two retail clients, and Inventale is currently looking for business opportunities for it in the following fields:

  • Shop assistant work evaluation
  • Analysis of merchandising and product display effectiveness
  • Control over queues and cash-desks zones
  • Promo effectiveness analysis
  • Optimization of business hours schedule
VideoSift