This video contains python implementation of Realtime Face Emotion Recognition
1) Brainstorming (background of facial emotion recognition)
(i)Challenges in FER 2013 dataset
2) OpenCV for drawing rectangles and overlaying text data
3) Face emotion recognition using DeepFace library
4) Live Video demo using OpenCV + DeepFace for Webcam

Taken from Joe Rogan Experience #1281 w/Tom Papa:
https://www.youtube.com/watch?v=mgLAhLzw2s8

In this video we will be using the Python Face Recognition library to do a few things

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Examples & Docs:
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https://github.com/ageitgey/face_recognition

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China is the world leader in facial recognition technology. Discover how the country is using it to develop a vast hyper-surveillance system able to monitor and target its ethnic minorities, including the Muslim Uyghur population.

Click here to subscribe to The Economist on YouTube: https://econ.st/2xvTKdy

Improving lives, increasing connectivity across the world, that’s the great promise offered by data-driven technology – but in China it also promises greater state control and abuse of power.

This is the next groundbreaking development in data-driven technology, facial recognition. And in China you can already withdraw cash, check in at airports, and pay for goods using just your face. The country is the world’s leader in the use of this emerging technology, and China’s many artificial intelligence startups are determined to keep it that way in the future.

Companies like Yitu. Yitu is creating the building blocks for a smart city of the future, where facial recognition is part of everyday life. This could even extend to detecting what people are thinking.

But the Chinese government has plans to use this new biometric technology to cement its authoritarian rule. The country has ambitious plans to develop a vast national surveillance system based on facial recognition. It’ll be used to monitor it’s 1.4 billion citizens in unprecedented ways. With the capability of tracking everything from their emotions to their sexuality.

The primary means will be a vast network of CCTV cameras. 170 million are already in place and an estimated 400 million new ones will be installed over the next three years. The authorities insist this program will allow them to improve security for citizens, and if you have nothing to hide you have nothing to fear.

But not everyone is convinced. Hong Zhenkuai is a former magazine editor who was ousted by the government. He feels like he’s under constant surveillance. Already the authorities are using facial recognition to name and shame citizens, even for minor offenses like jaywalking. In Beijing they’re using the technology to prevent people stealing rolls of loo paper from public toilets, and across China police officers are now trialing sunglasses and body cameras loaded with facial and gesture recognition technology – it’s helping them to identify wanted suspects in real-time.

What worries some people here is that as the technology develops, so too does the capacity for it to be abused. Some of those most at risk in this hyper surveillance future are the ethnic minorities in China. In Xinjiang province, the Chinese government is wary of the separatist threat posed by the Muslim Uyghur population. According to local NGOs, an estimated 1 million Uyghurs are being detained indefinitely in secretive internment camps, where some are being subject to abuse. It’s been called the largest mass incarceration of a minority population in the world today.

The authorities are using facial recognition cameras to scan people’s faces before they enter markets. The system alerts authorities if targeted individuals stray 300 meters beyond their home. In the future the government plans to aggregate even more data and build a predictive policing program that imposes even tighter controls here.

Without checks and balances, China will keep finding new ways to violate the human rights of its citizens. What’s already happening in Xinjiang is a warning the rest of the world must heed.

What are the forces shaping how people live and work and how power is wielded in the modern age? NOW AND NEXT reveals the pressures, the plans and the likely tipping points for enduring global change. Understand what is really transforming the world today – and discover what may lie in store tomorrow.

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There’s a massive bait-and-switch at the center of facial recognition technology.

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Human faces evolved to be highly distinctive; it’s helpful to be able to recognize individual members of one’s social group and quickly identify strangers, and that hasn’t changed for hundreds of thousands of years. Then in just the past five years, the meaning of the human face has quietly but seismically shifted. That’s because researchers at Facebook, Google, and other institutions have nearly perfected techniques for automated facial recognition.

The result of that research is that your face isn’t just a unique part of your body anymore, it’s biometric data that can be copied an infinite number of times and stored forever. In this video, we explain how facial recognition technology works, where it came from, and what’s at stake.

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Sources:
“Obscurity and Privacy” https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2439866
“Modern Face Recognition with Deep Learning” https://medium.com/@ageitgey/machine-learning-is-fun-part-4-modern-face-recognition-with-deep-learning-c3cffc121d78
“Face Recognition and Privacy in the Age of Augmented Reality” https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3305312
Megapixels https://megapixels.cc/about/
“FBI, ICE find state driver’s license photos are a gold mine for facial-recognition searches” https://www.washingtonpost.com/technology/2019/07/07/fbi-ice-find-state-drivers-license-photos-are-gold-mine-facial-recognition-searches/
“Are Stores You Shop at Secretly Using Face Recognition on You?” https://www.aclu.org/blog/privacy-technology/surveillance-technologies/are-stores-you-shop-secretly-using-face
“Due to weak oversight, we don’t really know how tech companies are using facial recognition data” https://www.fastcompany.com/90372734/due-to-weak-oversight-we-dont-really-know-how-tech-companies-are-using-facial-recognition-data
“Facial Recognition Service Becomes a Weapon Against Russian Porn Actresses” https://advox.globalvoices.org/2016/04/22/facial-recognition-service-becomes-a-weapon-against-russian-porn-actresses/
“Creeped out by Facebook’s algorithms? Just wait until you see this new facial recognition tool released by anonymous Russian programmers.” https://meduza.io/en/feature/2019/02/13/creeped-out-by-facebook-s-algorithms-just-wait-until-you-see-this-new-facial-recognition-tool-released-by-anonymous-russian-programmers
“How it works and why they created SearchFace – a service for searching VKontakte users by photo” https://tjournal.ru/tech/87841-kak-rabotaet-i-zachem-sozdali-searchface-servis-po-poisku-polzovateley-vkontakte-po-fotografii

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An automated typewriter that takes dictation.

A few details: Some code running on my laptop (off screen) uses Windows’ voice recognition to turn speech to text. Commands for the typing mechanism are then sent to the Pololu servo controller. The Arduino Uno and Big Easy Driver control the carriage return arm and are signaled when the new line routine is called.

The “arms” move on short linear rail segments. I cut the custom parts out of acrylic on a friend’s CNC (thanks to kiteandrocket.com).

John Oliver takes a look at facial recognition technology, how it’s used by private companies and law enforcement, and why it can be dangerous.

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Notes of FACE RECOGNITION SYSTEM in this link – https://viden.io/knowledge/face-recognition-system?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=ajaze-khan-1

An iOS app that can detect human emotions, objects and lot more. Made using coreML image detection API.

Thank you for Watching. Please don’t forget to subscribe.

~
## Inspiration

Inspired by a few blind people who use echolocation to “see” things around them, we have developed an interface that would help a blind person listen to have a feeling of where they belong in the society and enjoy the little things and experiences of everyday life.

## What it does

The interface is connected to a camera (which could be then possibly integrated with cameras on pen tips) which records real time videos of events, parse it into multiple frames – analyze it piece by piece and finally using a text to speech interface, dictates what it sees.

## How we built it

For Building the interface, we used the Apple Artificial Intelligence API that contains a pre-trained data set that could be readily used. However on experimenting we learned that real time video/image has a lot of noise, and that it would take a long time to train the data set for practical purposes. Therefore we created a small data set with real time images (taken using phone cameras) and further trained the available data set to a considerable degree of accuracy. With enough time, this can further be implemented and generalized into more diverse data sets, achieving its intended purpose.

## Challenges we ran into

As previously mentioned, we learned that the time it takes to train a simple data set is longer than we had previously anticipated. Therefore we had to restrict our data set and only work towards training specific limited amount of data.
We also tried using the Microsoft Azure API to integrate into our interface – however, we soon learned that we had a few dependency issues that we could not resolve. We wasted over seven to eight hours trying to get that to work. In the end, we moved to using the Apple’s AI API

## Accomplishments that we’re proud of

In the course of this Hackathon, we managed to code and implement successfully in 3 languages – Python, Java and ios. Even though we did not pursue our completed Python project to integrate into an android app (we had to download and learn to use a cross platform program to execute that) – we were able to successfully implement and get positive results in all three languages.

## What we learned

We learned various new methods of coding with AI and Machine Learning Algorithms. We also gained a clearer picture on how to use APIs and integrate them into a common framework that we had in mind. Also, in addition to that, we were also able to learn a bit of implementation using neural networks.

## What’s next for BlindCare

We hope to perfect our code in the future, so that it could be then used in various diverse environments. We are also trying to get to use pre-existing APIs and make the best use of them, therefore extending the reach and impact of BlindCare

This tutorial would help you understand Deep learning frameworks, such as convolutional neural networks (CNNs), which have almost completely replaced other machine learning techniques for specific tasks such as image recognition using large training datasets. In this webinar, we will go over how CNNs, their training methods, and hardware evolved since LeNet first appeared in the late 1990’s. We will examine the challenges that came along, and some key innovations that helped overcome these challenges. We will also look at a guide on how to get started with CNNs, some common pitfalls, and tips and tricks in training CNNs. Advanced Technology Group (ATG) of the CTO Office at NetApp. The ATG group is responsible for investigations, through early product prototypes, and leveraging technologies expected to become mainstream in 3+ years.

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Download:
The circuit diagram and Project programming can be downloaded by clicking on the link below

Arduino Image Processing based Entrance lock Control System

Download Libraries:
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Image Processing based Eyepupil Tracking:
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Human machine tracking using image processing:
https://youtu.be/HnKRy26NXMU

Watch other tutorials:

9: Image processing based entrance control system
https://youtu.be/TYllIMfJ3Eg

8: GSM and GPS based car accident location monitoring
https://youtu.be/tumEQioxT6I

7: GSM based GAS leakage detection and sms alert
https://youtu.be/Ar4LowNT_HI

6: Wireless Tongue controlled wheelchair
https://youtu.be/WNCn062YzXc

5: Human Posture Monitoring System
https://youtu.be/6bxZyTi6m-4

4: RFID based bike anti theft system
https://youtu.be/iGtu6TQ-_ao

3: RFID based students attendance system
https://youtu.be/gc4LLN1vftk

2: Piezo Electric generator
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Project Description:
********************

This is a very detailed tutorial on how to make image processing based human recognition system for entrance controlling. In this project we will be using Arduino uno for controlling the electronic door lock, The Arduino will receive command from the vb.net application when a human will be detected. We will be using xml file for human face detection. This xml file will be used in vb.net application to track a human face. The application designed in vb.net visual basic make use of the emguCv.

************************

download haarcascades:
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*********************

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how to make Arduino based image processing project that can detect a human and opens an entrance/door
image-processing based automatic door opening system using Arduino
Arduino image processing
Arduino vb.net emgucv
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Arduino Uno and image processing
mega and image processing
how to track a human face using emgucv /OpenCV Arduino
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how to track a human face and find its x y values
how to find the coordinates of the face using image processing

#CarControlAndAnti-theft
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Hello! Today I will show you how to make image recognition bots as fast as possible using Python. I will cover the basics of Pyautogui, Python, win32api and by the end, you should be able to make a bot for pretty much any game.

Here are the commands to run and code to paste: https://github.com/KianBrose/Image-Recognition-Botting-Tutorial/blob/master/README.txt

All code can be found here: https://github.com/KianBrose/Image-Recognition-Botting-Tutorial

If this video helped you please consider subscribing and leaving a like, it helps a ton!

If you have any errors/suggestions please let me know!

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Emotion Research LAB´s facial recognition software captures the emotions in real time of a consumer while testing a yogurt. The obtained data are included in the study along with the measurement of the emotions of the rest of the individuals. The final report includes the key metrics for observing the main satisfaction level.

Using previous pattern outcomes to help us begin to predict future outcomes.

Welcome to the Machine Learning for Forex and Stock analysis and automated trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex.

This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series.

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So I was messing around with voice recognition in the browser and I taught it would be quite fun to make an episode about it.

Disclaimer: This is not a super advanced AI like googles or Siri, it’s just me literally messing around with some code.

I used google chrome with a few new apis that are available for us to mess around with in javascript, one of them being the speech synthesis api.

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Make your own speech recognition app using MIT app inventor and control gadgets, electrical appliances, and robots. This app will allow you to control any gadgets I’ve made a working video of this app controlling electrical devices using arduino and HC-05 bluetooth module,. check out the video here https://www.youtube.com/watch?v=EJ0WEkG6zuY

circuit diagram and arduino program can find in the link http://mitappsinventor.blogspot.in/p/blog-page.html

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Android has an inbuilt feature speech to text through which you can provide speech input to your app. With this feature you can add some of the cool features to your app like adding voice navigation and it is very helpful when you are targeting disabled people.

In the background how voice input works is, the speech input will be streamed to a server, on the server voice will be converted to text and finally text will be sent back to our app. This tutorial can be followed by a beginner as the source code in github is also available.

Github Source Code: https://github.com/smartherd/SpeechToText/ .
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When you tap on Flow, the camera activates and Flow begins to analyze the objects you put in front of it.

There are many ways Glass can help simplify your life. And one of those daily chores is Grocery shopping. Either from the grocery store or right in your home, Glass, Cloud and Catchoom’s Image Recognition come together to make the perfect application of Glass in your every day life. Either from the grocery store – shop, scan, leave and your products get delivered to your home — or directly from your kitchen. This video shows how easy it is to grocery shop with Glass from your kitchen. Scan the product you need to replace, put it in your shopping cart, pay, check out and schedule delivery right from you kitchen. Glass, powered by Catchoom Glass SDK, puts your life right at your fingertips. Learn more about CraftAR Image Recognition: http://catchoom.com/solutions/image-recognition/

The new Moultrie camera system features an updated MV2 modem and an integrated camera which is the XV7000i. It also features an Image recognition software that allows you to sort images by their content.

◄ Language English – 720p – Cortana problems
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Cortana problems – setting problem – speech recognition [FIX]

You are here because you have problems with Cortana on Windows 10

Check the video.

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Everybody knows that Windows Vista Speech Recognition was terrible, but just how much of a train wreck was it? Well, lets put it to the test! Can Ben write a story about a boy who goes to the shops to buy a packet of chips and a toy car, using speech recognition? Hehe, you might find that the computer decides to take the story in its own insidious direction.

This task was Suggested by Patreon Donator, William Eiberg, so be sure to check out his channel: https://www.youtube.com/user/williameiberg/featured

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OSFirstTimer Advanced ditches the original 5 basic tasks and introduces a new random advanced task each episode. The task can involve literally anything from video editing to 3d modelling to programming and even attempting to destroy an operating system.

Random tasks using random software in random operating systems from random time periods… now this will be a lot more interesting! Don’t worry though as we may occasionally go back to our roots and do a few “original series” episodes.

I hope you guys enjoy this episode and look forward to whatever crazy task we do next episode on OSFirstTimer Advanced.

Using previous pattern outcomes to help us begin to predict future outcomes.

Welcome to the Machine Learning for Forex and Stock analysis and automated trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex.

This is especially useful for people interested in quantitative analysis and algo or high frequency trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series.

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Introducting EarthCam’s AI-powered recognition technology for identifying obstructions and performing quality control for premium time-lapse content. Using its newly-developed AI algorithms, EarthCam is currently able to process over half a million high-resolution images a day to detect if camera images are obscured by foreign objects, dirt, fog or have the presence of rain droplets on the lens. The smart software looks for 16 different components in an image, both desirable and unwanted features, and then creatively re-edits the video. Cost savings are immediately realized with instant access to presentation-ready time-lapses, free of expensive editing processes and production wait times. Clients will still enjoy hand-edited time-lapse videos at the end of their project and can now download entertaining AI-edited movies at any time on-demand. The unique videos come complete with music and on-screen graphics, to present informative updates to stakeholders and share social media-ready content for public outreach.

Augmented Reality image recognition with Vuforia SDK. Placing 3D animated model on top of recognized image pattern inside of school book. www.creatifesprit.asia

Take a look at Junaio Glue’s new feature – the ability to recognize images in real-time and overlay objects on that image. The feature has been available for Android, but only with iOS 4 has the iPhone been able to do image recognition in augmented reality (AR) apps like Junaio.

Use Bixby Image Recognition to identify and find similar images of any picture on your phone or taken with your camera. Great for identifying unknown plants, toys, objects and more.
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Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML

A friendly explanation of how computer recognize images, based on Convolutional Neural Networks.
All the math required is knowing how to add and subtract 1’s. (Bonus if you know calculus, but not needed.)
For a brush up on Neural Networks, check out this video: https://www.youtube.com/watch?v=BR9h47Jtqyw

Demos of the PC speech recognition applications Google Voice Search, TalkTyper.com, Windows Speech Recognition, and Dragon NaturallySpeaking.

The “Computing Health & Safety” and “Beating RSI” videos referred to in this video can be found here:

http://www.youtube.com/watch?v=T8qGO7XQ0Uw and
http://www.youtube.com/watch?v=3DR9fAQuOK8

The free online TalkTyper application can be found here:
http://www.talktyper.com

You may also find useful my “Top 10 Tips for RSI” video here: https://www.youtube.com/watch?v=2FVb0vj51sQ

More computing videos can be found on the ExplainingComputers YouTube channel at: http://www.youtube.com/explainingcomputers

You may also like to visit our sister channel, ExplainingTheFuture, at: http://www.youtube.com/explainingthefuture

Jeff Dean, lead of Google AI (Google’s artificial intelligence effort) explains what happens when you use OK Google’s artificial intelligence speech recognition. Want to learn more about AI? Try the Curiosity Machine AI Family Challenge: https://www.curiositymachine.org/

In this video am going to show a new development board, the Sipeed M1 Dock which features the revolutionary $10 K210 AI chip. Just like the ESP32, this chip is going to change everything, bringing hardware AI to the maker community.

🛒 Sipeed M1 Dock: http://educ8s.tv/part/SipeedM1
🛒 Maixduino: http://educ8s.tv/part/maixduino
🛒 Power Meter: http://educ8s.tv/part/UsbDoctorOLED

💖 Full disclosure: All of the links above are affiliate links. I get a small percentage of each sale
they generate. Thank you for your support!

📥 Firmware: https://github.com/sipeed/MaixPy/releases/download/v0.3.2/maixpy_v0.3.2_full.bin
📥 K Flash GUI: https://github.com/sipeed/kflash_gui/releases
📥MaixPY IDE: http://dl.sipeed.com/MAIX/MaixPy/ide/v0.2.2/maixpy-ide-windows-0.2.2.exe

📥 Code: http://educ8s.tv/sipeed-m1-dock-review

🔗 Website: https://www.educ8s.tv
🛒 Store: https://teespring.com/stores/educ8stv-store

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Quiz of Knowledge Android Game
——————–

You can download my latest Android Game which is called Quiz of Knowledge here:

📥 http://bit.ly/QuizOfKnowledge

A handful of US cities have banned government use of facial recognition technology due to concerns over its accuracy and privacy. WIRED’s Tom Simonite talks with computer vision scientist and lawyer Gretchen Greene about the controversy surrounding the use of this technology.

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Why Cities Are Banning Facial Recognition Technology | WIRED

https://play.google.com/store/apps/developer?id=FineLineLabs

Computer Vision. Object Recognition. Android Eye. Take a Picture of any Object.
Android Eye is the first Object Recognition App. Take a picture of any object, and Android Eye will tell you what it is.
Computer Vision. Image Recognition Technology (IRC).
Take a picture of a car… Android Eye will tell you the make and model of the car. Take a picture of a foreign t-shirt label… Android Eye will tell you the brand, and where the shirt is from. Take a picture of a tree… a ball… a person… the results are endless.
It works very well, particularly with vehicles, products, brands, and well-known “things”:)
Software that does this is usually only available to government agencies and research facilities. I will soon release the code “open source”, once it’s been on the market for a bit:)
As versions are updated, the cost may go up, but for now it’s FREE (amazing!)
Enjoy, and learn with it:) Ideal for visually impaired persons. Ideal for identifying vehicles or other manufactured items including computers, phones, or anything you would like a name for, a make or a model:)

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