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Project

Facial Recognition

Dec 5, 2019

 

Skill Level Area of Focus Operating System Platform/Hardware
Advanced Computer Vision, Facial Recognition, Embedded, Security, Smart Cities Linux DragonBoard 410c

This project utilizes the power of the DragonBoard™ 410c from Arrow Electronics to run a facial recognition application, utilizing libraries like Caffe2 and OpenCV.

Objective

The main goal of the project is to demonstrate the power of the DragonBoard 410c to run a modern computer vision application for facial detection and recognition. Using powerful libraries like Caffe2 and OpenCV, the software finds faces in the image and use a DNN to classify the person.

Materials Required / Parts List / Tools

Source Code / Source Examples / Application Executable

Build / Assembly Instructions

The build instructions can be found in the README file in the GitLab link. Basically, you have to build the libs and install the application on the board.

Usage Instructions

Setup the webcam to scan your environment and find faces. Run the project as described in the GitLab link. The application will show a screenshot in the monitor periodically and will mark the faces detected with a bounding box. Names of recognized people are shown in the screen, and new people are tagged as unknown.

Project

Opinions expressed in the content posted here are the personal opinions of the original authors, and do not necessarily reflect those of Qualcomm Incorporated or its subsidiaries ("Qualcomm"). The content is provided for informational purposes only and is not meant to be an endorsement or representation by Qualcomm or any other party. This site may also provide links or references to non-Qualcomm sites and resources. Qualcomm makes no representations, warranties, or other commitments whatsoever about any non-Qualcomm sites or third-party resources that may be referenced, accessible from, or linked to this site.

Project Authors
AugustoQualcomm IoT Reference Center - FACENS
FelipeQualcomm IoT Reference Center - FACENS
Lucas MaxQualcomm IoT Reference Center - FACENS
Lucas MendesQualcomm IoT Reference Center - FACENS
Luccas SchardtQualcomm IoT Reference Center - FACENS
StephanieQualcomm IoT Reference Center - FACENS
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