MagicMirror RealSense Module

MagicMirror RealSense Module

Andre Carlucci

Andre Carlucci

Saco Grande, Santa Catarina

A facial recognition and multi-user module for MagicMirror2 using the RealSense Camera.

Intel RealSense™, Internet of Things

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The idea is very simple: add a small board and a monitor behind a two-way mirror and code some software to provide useful information to the person in front of it.

I’ve seen on the Internet some implementations of this, but I wanted to provide personalized information to the person in front of it using a camera and facial recognition algorithms. Something like providing commuting time and next appointments for me and change the information when my wife would stand in front of it.



Blog post about the project

WpfApp for facial Recognition using RealSense

MagicMirror2 RealSense Module

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Peter M. created project Smart City Air Monitor

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Smart City Air Monitor

Smart City Air Monitor uses air quality sensor attaching to the vehicle to monitor the air quality through out the city. This idea originally came from Pigeon Air Patrol, where they use pigeon to monitor air quality in London. We believe that using our own cars would have much better results. A pubnub will be sending push notifications for those who enters the polluted areas. It would provide 3 major benefits

1) For the drivers, they can now avoid heavily polluted areas and find alternative routes, it also allows them to monitor pollution during time of the day.

2) The drivers now are also providing the air quality data to the city so that everyone else can plan their days around it.

3) The city now knows where the most heavily polluted areas are, so that they can install air filters, trees, or simply signs to warn other citizens the general air quality around that area.

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donel a. updated status

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donel adams

Google or Bing name to view associate networks fostering business development by maximizing any platform potential for growth utilizing AI

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Dhruv R. created project Business Card Scanner

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Business Card Scanner

Here’s how it works:

It uses Google’s Tesseract to built an Optical Character Recognition Engine inside the phone once installed, thus it works completely offline.

Then using Leptonica Image Processing and various other algorithms the image clicked is enhanced so as to best suite for the OCR purpose.

The engine then extracts the text which undergoes entity detection using Open Natural Language Processing(OpenNLP).

The entities are put under appropriate fields and the contact is saved in the phone directory along with the business card.

Using Parse as backend, Android Studio as IDE, stackoverflow as mentor I finally completed the app in 1 month time period.

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Dhruv R. updated status

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Dhruv Rathi

Fishes classification from under water is a huge problem for fishermen and survey guides, organisers and government itself. I am working on a new algorithm to classify fishes based on textures from underwater images into the corresponding species.

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Alexander H. updated status

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Alexander Holman

An AI you can have a conversation with. A routing engine for Taxi companies. A new C based programming language (to learn). Lots and lots of websites and apps.

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Sagar P. updated status

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Sagar Patel

Developing a Reversi Android Application. Implementing versions of the MiniMax algorithm with Alpha-Beta pruning to create an AI player.

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Gokula Krishnan Santhanam

Masters student @ ETH Zurich, Deep Learning Researcher working on both fundamentals and applications of Deep Learning technologies.

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Mate Kisantal

Machine Learning oriented Aerospace Control Engineering student, with some experience in self-driving car control design.

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perry obara

I'm always ready to learn.

Nairobi, Kenya

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Victor Kinoti

python programmer, telecommunications eng.

Nairobi, Kenya

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Shuo Liu

I am studying electronic engineering at University of British Columbia (Okanagan Campus ), Canada.

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Akhilesh Rao

2360 SE Morrison St, Portland, OR 97214, USA

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