Blog

Learn About Our Meetup

5000+ Members

MEETUPS

LEARN, CONNECT, SHARE

Join our meetup, learn, connect, share, and get to know your Toronto AI community. 

JOB POSTINGS

INDEED POSTINGS

Browse through the latest deep learning, ai, machine learning postings from Indeed for the GTA.

CONTACT

CONNECT WITH US

Are you looking to sponsor space, be a speaker, or volunteer, feel free to give us a shout.

[D] Creating a Face Verification algorithm for authentication

Hello guys!

I’ve just started working on a small project that involves analyzing a web cam generated image and compare it to images on a dataset folder to try and find a match.

There are some pre-trained models out there, which enables one-shot learning (like this GitHub for example: https://github.com/mohitwildbeast/Facial-Recognition-Using-FaceNet-Siamese-One-Shot-Learning)

However, it is not precise as I wanted, and I don’t really know why.

I was looking the FaceNet model by David Sandberg (https://github.com/davidsandberg/facenet) and it seems promising, however I don’t know how to use it for my case.

So, I was wondering if you guys have any advice for me, any link, that might help me!
The system should be simple, is just a proof of concept, so as long as the algorithm can compare the face it is detecting on the webcam, for example, to one on a images folder and return the embedded distance (distance between the faces, where smaller are similar faces and bigger otherwise).

I’m not sure if I was clear, as it is my first time writing on this sub.

Thank you all in advance.

submitted by /u/Berdas_
[link] [comments]

Next Meetup

 

Days
:
Hours
:
Minutes
:
Seconds

 

Plug yourself into AI and don't miss a beat

 


Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.