Intelligent Digital Signage Solution

Determine the demographics of an audience using the Intel® Distribution of OpenVINO™ toolkit, and then adjust the ads to match the audience.

Target Operating System: Ubuntu* 16.04 LTS

Time to Complete: 45 minutes

Software Used:

Intel® Distribution of OpenVINO™ Toolkit

Intel® Media SDK

Intel® System Studio

Models Used:

face-detection-retail-0004

age-gender-recognition-retail-0013

head-pose-estimation-adas-0001

GitHub* (C++)

What You Will Learn

Using a video camera as part of a digital kiosk system, this application identifies the age and gender of the audience standing in front of a digital sign. Based on the identification, the application selects a suitable 4K advertisement. Real-time data visualization occurs on Grafana*, which enables developers to monitor trends over time.

Gain insight into the following solutions:

Computer vision applications for IoT
Inference to analyze datasets
Retail market IoT

Learn to build and run an application with these capabilities:

❶ Determine age, gender, and head pose with deep neural network (DNN) models.
❷ Play a 4K ad based on audience identification.
❸ Visualize analytics using a combination of InfluxDB* and Grafana.

How It Works

This application works as follows:

❶ Detects faces in the frame of interest using a DNN model.
❷ Uses two other DNN models to determine the age, gender, and head pose position for each face.
❸ The model output provides audience demographics, and based on a predetermined table included in the JSON file, determines the appropriate ad to be displayed.
❹ The ad is decoded and played using the high-efficiency video coding (HEVC) plug-in included in the Intel® Media SDK.
❺ The number of viewers, unique visitors, and gender of visitors is stored in the InfluxDB and displayed using Grafana.
The DNN models are optimized for Intel® architecture and are included with Intel Distribution of OpenVINO toolkit.