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A Bit About: Enhanced Facial Image Capture

Watch Axis Communication's Stephen Joseph and Parabit's Rob Leiponis discuss the benefits of optimized video surveillance sensor placement, and how it can have a major impact on security and retail engagement.

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Hilary Kennedy: Hey there, welcome to A Bit About, a Parabit Systems podcast. I'm your host, Hilary Kennedy, and today's episode is going to dive into how technology is enabling a smarter and safer world by creating network solutions that provide insights for improving security and some new ways of doing business.

And I have two great guests joining me on the show today to share their insight. First, Rob Leiponis, President and CEO of Parabit Systems, which is a leading global provider of innovative hardware and software solutions serving critical infrastructure. And since founding the Long Island based company in 1995, Rob has driven the development of technology deployed by hundreds of financial institutions throughout North America and Europe. And Rob draws on tremendous experience that spans 35 plus years.

And then our second guest is Stephen Joseph, Segment Development Manager of Banking and Finance of Axis Communications. And Steven is responsible for strategy development for the banking segment, education development for internal and external customers. He speaks at national conferences and has a host of other critical roles. So it goes without saying that both of them will have a wealth of knowledge to share on improving security, and how cameras are enabling data analytics that the world needs.

So welcome to the show, gentlemen.

Stephen Joseph: Hi Hilary, thank you.

Rob Leiponis: Thank you.

Hilary Kennedy: Alright, so first, I want to start off with effective facial image capture. It supports safety and security, as well as you know, retail and marketing. So what are some of the challenges, though, when it comes to capturing good facial images?

Stephen Joseph: Well, for the most part, capturing good facial images are really important, especially when you're dealing with customer-facing environments. Specifically, and for me, it's most of the time in the banking and finance institutions, and it can also be in retail as well, where you see customers coming on a regular basis. And one of the main challenges that a lot of these businesses have is being able to place cameras at an optimal location to be able to capture great facial images.

When incidents occur, and law enforcement is called in and they need to capture or be able to get evidence as it relates to who may have perpetrated a crime, being able to have that optimal image to be able to recognize and provide forensic detail is really, really important in those use cases.

Hilary Kennedy: And, Rob, do you have any thoughts on that too? You know, what are some of those challenges when it comes to capturing good facial images.

Rob Leiponis: Just basically eliminating any type of obstructions that can come from any existing cameras that they would like to leverage for analytics, to installing or repositioning a more discreet camera that's closer to the actual face to eliminate the possibility of someone coming in obstruction, of all the images of the people's faces as they walk in and out of retail facilities, transportation hubs, you know, loading docks and logistics facilities.

I think it's important, from an access control perspective, from an artificial intelligence perspective, to be able to leverage that technology that's so great, and that's been helping create such a life-safety environment for the world. To be able to maximize the investment by placing those images in the sensors close to people's faces.

Hilary Kennedy: It's so true. It's helped in so many countless different situations, especially where safety's involved. And I heard both of you mentioned analytics and so Steven, I want to direct this at you can you give an example of the capabilities of analytics when effective facial image capture is achieved?

Stephen Joseph: Absolutely. There's a lot to know with regards to facial capture. People use the term interchangeably, but there are different levels of capturing faces. You have traditional face capture where you just you know, capturing an image of a person's face, you know that it's an individual, whether it's male or female. You have facial detection, where you're able to actually detect that it's a face. Facial recognition, being able to recognize who that individual is. Facial identification, where you're actually able to, with 100% certainty, be able to determine that that individual matches face that you currently have in some type of database.

And you see this a lot in law enforcement where they're looking through databases, and we see this a lot on TV where you see somebody looking through a mug shot book, right? They're trying to do forensic identification. And they're comparing faces that are known faces, to help someone identify that person.

And when you have proper placement of cameras or video cameras in these cases, and if you walk into most establishments, today, you're going to see a camera. It's either going to be on the ceiling, or it's going to be on a wall. Normally, it's far back from where that person is actually standing. But the types of topics that we're trying to discuss today has to do with having a proper placement of an image sensor that allows you to get a great shot of a person's face.

When it comes down to facial detection, you need about four pixels. And you think about pixels and you think about let's say 1080P or 4k television, there are pixels in that image. You need about four pixels across a person's face to actually get facial detection. In order to get facial recognition you need about 20 pixels across the face. To do identification, you need about 40 to 80 pixels across the face. So that gives you an example of the different levels of facial capture, facial detection, that you can look be looking for.

Hilary Kennedy: Well it's so interesting, because you can't go in any store anymore without you know being able to see the cameras. So Rob, I would love for you to tell us a little bit about when it comes to retail and marketing. How is facial image capture the most beneficial there?

Rob Leiponis: So, facial capture is good for determining what type of content that you may want to display on various digital signage, or sending messages to tellers in a platform that a certain person with a certain profile has walked in, or back they may be a customer of yours. So that way you can target or create more targeted questions in order to convert that customer to a better service that they may be providing for them.

Notification of a customer arrival like in a Nordstrom experience where you know when a customer arrives, there's a sales rep that's assigned to that person every time they walk into the store. Through analytics, that person could get notified immediately that their premier customers are walking in the southeast entrance of the building and provide a better greeting experience for them.

Hilary Kennedy: And something that I want to touch on because we can't have this conversation without talking about AI. So Steven, you know, we've got some new developments in how we operate as a society that have come out of the pandemic such as mask wearing so how does deep AI come into play where cameras are concerned?

Stephen Joseph: Oh, it comes into play in a big way. I mean, AI is a really really big topic. You know, we see a lot of interest in the area of AI or analytics as it relates to behavior. So whether it's utilizing video surveillance products to do sound detection, to run analytics to count people. We see it a lot with facial detection analytics to do things like capture facial expressions to determine whether or not your customer is happy or not. And we we see this going on today and this technology exists.

And during the pandemic we had partners that were actually utilizing or trying to test out their analytics that we were traditionally used for security use cases, and taking them to actually use them for things like social distancing. Trying to detect whether someone was actually wearing a mask or not. And then taking that information and using it to drive back-end systems, so you can have system integration with other systems. Let's say people are waiting in line a long time being able to trigger and play music, let's say in a lobby area where people are waiting inside of financial institution or even in a retail shop.

So analytics or AI is really being used in a lot of different ways, and there are a lot of different use cases that are being developed every single day.cCstomers or businesses are starting to find new ways to utilize AI and analytics in ways that we've never even thought of before.

Hilary Kennedy: That really is fascinating and I love the use of it to find out if your customers are smiling and happy. I love that because you know they're gonna do what they can to keep you there and feeling good.

Stephen Joseph: Absolutely.

Hilary Kennedy: So Rob, I want to ask you this question the proper placement of cameras that is critical to the effectiveness of the analytics and of course the demand for analytics just keeps increasing. So what are some enclosure types that should be considered?

Rob Leiponis: Our most popular unit that we see moving mostly is our doorway cameras. I mean, placing doorway cameras around any entrance or exit way gives you complete control from, as Steven mentioned, AI and facial analytics and knowing, as you said, whether a person's sad or happy as they're entering or exiting a facility. So it's really a key to me. A very key position point as well as transaction points.

You know, as you're developing other retail experiences when the person is there the actual cashier can be receiving messages because they know who you are your approach and suggest additional sales. So you know, really at the point where people are spending, entering and exiting facilities, as well as those transaction points, I think are really key places to place covert or the discreet cameras that Axis sells.

Hilary Kennedy: Incredibly helpful. Well, Steven, I would love for you to share with us a few security success stories within some of the industries that you serve.

Stephen Joseph: Well, we've done several different pilots utilizing video surveillance and analytics using proper camera placement. One of the most important ones is being able to detect loitering with analytics and proper camera placement. We see this a lot, especially in financial institutions, where you walk into an ATM lobby, and there might be somebody hanging out in there, a suspicious character or whatever the case might be. And especially happens in cold climates, where people coming out of a cold to stay warm. You know one, it poses a security problem. A potential security problem and also poses a potential customer safety issue, or customer experience issue.

So we helped a major financial institution within the northeast to deploy some of our video surveillance products properly placed in the right place with the use of analytics to be able to detect loitering inside an ATM vestibule. So that one, it creates a safe space for customers to come in. You start dealing with different key stakeholders. So you have security, you have operations, you have an overall marketing aspect for you know, being able to protect your brand when you can have a safe environment for customers to come into. So it creates a better customer experience.

And also we worked with some major ATM manufacturers to be able to integrate video surveillance products and place them around the fascia of ATMs to be able to capture faces when people are standing at the ATM. Because normally what happens is someone will come in, especially a perpetrator, will come in with a baseball cap on they'll tilt their head down. So being able to place image sensors or cameras at the proper placement at an ATM helps a lot with being able to capture faces at an ATM. So that solves a big problem for them. Because then they get great information, great forensic detail, and they have good evidence to turn over to a law enforcement.

Hilary Kennedy: It's a great example, because I think all of us have gone to an ATM and gone inside and seen some people hanging out and thought like, “Oh, I don't know,” especially if you're withdrawing a lot of cash. So that's a great example. And one thing I want to touch on before we wrap up, you know we've seen a lot of stories about e-commerce and those kinds of things, but let's chat about the use of these technologies in those brick and mortar locations. Why is that so important?

Stephen Joseph: Well, it's definitely important because we see a lot of, there's a challenge, right? More people, especially with the pandemic, we saw the use and the need for online e commerce, right? But then again, it does create a challenge for brick and mortar operations. Nobody wants to see their favorite retail shop go away. So again, utilizing analytics and video surveillance and proper placement of products really helps create the ability to capture data, to be able to take that data, ingest it, and then utilize it to get information to know how many people are coming into a retail shop.

Do I need to kind of downsize the retail shop? Maybe I don't need to have as large a retail space as I used to. Maybe I just need to have a smaller space. But you still need a place where customers want to go and they feel comfortable. Sometimes people still want that ability to go in and touch, right? They want to be able to have hands-on with that product. So we don't want brick and mortar to go away, but we do want when customers come into those environments, to take what used to be traditional security products and use them in a smarter way.

So we're creating a smarter, safer environment for the customer. We're able to capture data, and we're able to create an overall better experience for those customers when they do come into those brick and mortar spaces.

Hilary Kennedy: Well, I have loved this conversation today because I feel safer already having spoken to the two of you. So, that is going to wrap up this episode of A Bit About, but I do want to say thank you again to Rob Leiponis with Parabit Systems and Stephen Joseph at Axis Communications, for joining me today and sharing your insight. Thank you so much.

Stephen Joseph: Thanks for having me.

Rob Leiponis: Thank you.

Hilary Kennedy: And I want to thank all of our listeners and watchers for joining us for the episode. We always appreciate it and if you would like more episodes of the podcast, and to stay up to date with everything that we have coming out in the future, make sure to subscribe on Apple podcasts or Spotify or wherever you prefer to listen to podcasts.

We’ll be back soon with another episode, but until then, I have been your host Hilary Kennedy.

Thank you for watching.


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