Insights to the customer behavior on store premises unlock enormous value to retailers.
The store chain client wanted to track the number of people walking in and out of her stores as well as their behavior inside the store.
Our team has built a solution that through a video camera tracks where people walk inside the store, identifying their gender and age category. The above had to be calculated in real-time using the setup located in the store – Dual Core Celeron + GTX 660 2Gb.

Months

Engineers

Technologies

Tech Stack

GStreamer

OpenCV

Python

YoloV2 Darknet

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Timeline

1 week

Data Labelling and Processing

Data Engineer

1 week

Solution Architecture Design

Solution Architect

2 weeks

Hypothesis Generation & Validation

Deep Learning Researcher

1 week

Architecture Modelling

Deep Learning Researcher

3 weeks

Training & Tuning Cycle pt.1

Deep Learning Researcher

2 weeks

Model Optimization

Deep Learning Engineer

2 weeks

Training & Tuning Cycle pt.2

Deep Learning Researcher

3 weeks

Video Streaming Backend Development

Backend Developer

Data Engineer

3 weeks

Web Development

Backend Developer

Frontend Developer

1 week

Integration & Deployment

Dev Ops

Tech Challenge

Since in 2016 there was no mobilenet yet, our team had to find a real-time solution for Detekces with significant capacity constraints as well as a solution for real-time video streaming with minimal loads.
Additionally, all data had to be cast into a dashboard displaying statistics.

Solution

Our solution has optimized Darknet YoloV2 and achieved 15 FPS, which was enough to solve the problem.
For real-time streaming we used GStreamer which we optimized for the in-store setup mentioned above.

Impact

As a result of our development, all meta information from the cameras was processed locally and had flown into the cloud.
From there, the store store chain could see the detailed statistics on the number of customers inside the store, as well as their distribution by age category and gender, allowing for smarter marketing and customer service decisions.

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Author

Yuliya Sychikova

COO @ DataRoot Labs

Yuliya is a co-founder and COO of DataRoot Labs, where she oversees operations, sales, communication, and Startup Venture Services. She brings onboard business and venture capital experience that she gained at a leading tech investment company in CEE, where she oversaw numerous deals and managed a portfolio across various tech niches including AI and IT service companies.

Co-Authors

Ivan Didur

CTO @ DataRoot Labs