greenwaves-technologies / facereid

Intro

The project is aimed to create and deploy a smart doorbell application that would be highly energy-efficient. The main application pipeline consists of 4 stages: frame capture, face detection, face recognition and user interaction e.g. displaying message. In addition to regular face detection and re-identification loop, application provides functionality to add known people to the trusted list using already calculated face descriptors.

Target Platforms

The demo is targeted for two boards Gapoc A v2 and Gapuino v2 and GAP SDK release 3.6 and 3.7.1. GAP8 V1 chips are not supported in SDK any more. List of extra components is provided below.

For Gapuino board:

• HIGHMAX camera module
• Adafruit 2.8 TFT display with SPI interface

For Gapoc A board:

• Adafruit 2.8 TFT display with SPI interface
• GAPOC_A Adapter for Adafruit LCD 2.8 version 3 or version 4 or hand-made shield with push button
• Android-based smartphone with pre-built user management application

Documentation Pages

• Hardware configuration and schematics
• Build and test instructions
• Pipeline overview
• ReID train instruction
• ReID network quantization for GAP
• ReID network architecture and inference details
• Bluetooth LE protocol for users management

Papers

• 512KiB RAM Is Enough! Live Camera Face Recognition DNN on MCU: link

@InProceedings{Zemlyanikin_2019_ICCV,
author = {Zemlyanikin, Maxim and Smorkalov, Alexander and Khanova, Tatiana and Petrovicheva, Anna and Serebryakov, Grigory},
title = {512KiB RAM Is Enough! Live Camera Face Recognition DNN on MCU},
booktitle = {The IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2019}
}

• GreenWaves press release and demonstration video: link

facereid's Issues

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