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  • Hi, I'm Martin Kronberg, and this is the IOT Developers'

  • Show where we look at IOT technology,

  • shared learning opportunities, and showcase cool demos

  • and the creators behind them.

  • In this episode, we're going to be

  • taking a look at an awesome facial recognition

  • and detection demo with Tudor Panu, a software engineer

  • here at Intel.

  • Let's get started.

  • Tudor, thank you so much for joining us.

  • What do you do here at Intel?

  • Hi, I've been a software engineer with Intel

  • for a little over three years now,

  • and I focus mostly on tools for IOT developers.

  • Before Intel, I got a PhD in computer science

  • and engineering from SMU in Dallas, Texas.

  • All right, cool.

  • Well, do you want to tell us a bit more about the demo

  • that you have for us?

  • This application is called face access control

  • and can be used for facial detection and recognition.

  • There are two main components, a video streaming service,

  • which includes the computer vision elements,

  • and a user based interface for registration and analytics.

  • In this set up, I used Intel's Computer Vision SDK

  • and a sixth generation Core i7 Intel NUC with a web camera.

  • Awesome.

  • Well, I'd love to see how it all works.

  • Let's check it out.

  • Let's take a look.

  • I'm going to use my own face to show you how it works.

  • First, you have to add your information to the database.

  • All you have to do is click the new profile button

  • when you're ready to save your picture.

  • Once the camera sees a face, it's already tracking you.

  • Thus, you can register a new person in real time

  • with a single click.

  • Here, I am entering the information in the database

  • to get through registration.

  • Since not all fields are mandatory,

  • I will just add my name and clearance level.

  • OK.

  • So you can basically assign different access levels

  • to people depending on their roles.

  • Exactly.

  • The clearance level really asks you

  • to access control side of the story

  • and can be used to trigger events such as opening a door

  • or sounding an alarm.

  • Let's see how it works.

  • You can see my profile picture pop up there

  • on the left with my name.

  • OK, it looks like it can easily recognize you.

  • Yeah, it's pretty accurate.

  • Let me show you the analytics portion of the application.

  • Every time a face gets detected, a new data point

  • is added to the chart.

  • You can also look at exact counts and distributions

  • on this screen.

  • Timestamps are also available on the side panel.

  • All right.

  • Well, I really like this interface that you've created.

  • How do you think the developers can

  • use an application like this?

  • So, the application will obviously

  • be used in digital surveillance and security.

  • However, there are some other verticals

  • that can be touched with it such as smart retail, smart cities

  • and buildings, and even robotics.

  • For instance, think of membership

  • based services like a gym.

  • You might want to send push notifications to your clients

  • whenever they don't show up for a while,

  • or if you have a large retail store

  • and you have a list of banned people,

  • you might want to alert security whenever somebody

  • from that list shows up.

  • Sure.

  • Maybe like known shoplifters that

  • have been caught in the past.

  • Exactly.

  • So, you mentioned that this application

  • is built using the CVSDK.

  • Is that right?

  • Correct.

  • We do use the open CV version that

  • comes with Intel's Computer Vision SDK,

  • and that library also includes the facial detection

  • and recognition algorithms.

  • These are faster than traditional methods,

  • and we can do detection or recognition almost

  • on every frame with low light SD.

  • So, what kind of system would I need

  • if I wanted to run this demo?

  • Any old bluetooth 1604 system that

  • supports the Computer Vision SDK will run it,

  • and you can also scale from Atom to Core to Xeon

  • based on your performance requirements.

  • Wow.

  • Well, this is a really cool Computer Vision demo.

  • If you guys are more interested in learning

  • about the specifics of the demo or how

  • to apply it into your own project,

  • we're going to provide all of the links.

  • Tudor, thank you so much for being here and showing

  • this demo off.

  • Thanks for having me, Martin.

  • Before signing off, I want to tell you

  • guys about some IOT news.

  • Recently, we launched the Intel E workshop.

  • Now, this is a virtual lab that walks you

  • through the set up of an Intel LG gateway with a sensor kit

  • to be able to read sensor values and then

  • publish that data to the cloud.

  • Also, recently we launched the Up Squared Grove IOT Developer

  • kit.

  • Go to the Intel Developer Zone for IOT

  • to get resources and tutorials to be

  • able to help you reduce development time for your IOT

  • applications.

  • Thanks for we're watching this episode of the IOT Developer

  • Show.

  • Don't forget to like this video and subscribe to the Intel

  • software YouTube channel.

  • Remember to check out the resources

  • and the links provided as well.

  • Thanks, guys.

Hi, I'm Martin Kronberg, and this is the IOT Developers'

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IoT デベロッパーショー|2017年11月|インテルソフトウェア (IoT Developer Show | November 2017 | Intel Software)

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