Video AnalyticsIoT Analytics Tailored To Meet Unique Business Needs

Video Analytics from Gorilla Technology inner image

What Video Analytics Does

The processes involved in getting IVA output from software is similar to how people visually detect and recognize things. The essence of what video analytics does is generally described in three steps.

  1. Video analytic software breaks down video signals into frames. Understanding digital video and how it works is an interesting topic and good to know before we break down the next steps.
  2. The software then splits the video (frames) into video data and analytic data, then uses algorithms to process the analytic data to output specifically desired functions.
  3. And finally, it delivers the result in a predetermined manner.
Image showing working through the video analytics process on a whiteboard.

Approaches to Video Analytics Processing

Depending on the goal, video needs to be processed using different methods in order to deliver relevant results. Gorilla has categorized the most widely used types of analytics into five fundamental IVA groups which are described in more detail below.

Behavior Analytics

These analytics use algorithms that are designed to look for a specific behavior.

Thinking more deeply, a behavior could be defined as action over time. With that in mind, each Behavior Analytic needs more than one frame from the video to determine if an event or behavior has occurred. So it follows that the algorithms in Behavior Analytics look for changes from frame to frame over time to identify a very specific and predefined event or action. We've broken down and classified the Behavior Analytics that are used in our solutions here:

People Counting

Image showing people counting video analytics from Gorilla Technology.

The People Counting IVA does just that, it detects and counts people for a specified amount of time as they enter a zone and/or cross a line which users define in the software.

Line Crossing

Image showing line crossing video analytics from Gorilla Technology.

This IVA detects when people cross a line (or lines) of user defined length and position.

Intrusion Detection

Image showing intrusion detection video analytics from Gorilla Technology.

Intrusion Detection monitors user created zones to detect any activity or entries by moving objects (like people).

Direction Detection

Image showing direction detection video analytics from Gorilla Technology.

This IVA monitors a user created zone for people moving A) within the zone AND B) in the marked direction. Movements in the opposite direction do not trigger an alert.

Direction Violation Detection

Image showing direction violation detection video analytics from Gorilla Technology.

Same as the direction detection IVA but detects and alerts to movements in the opposite direction. As an example, security checks at airports and other transportation hubs stand to benefit from this type of IVA.

Loitering Detection

Image showing loitering video analytics from Gorilla Technology.

The Loitering Detection IVA monitors figures or people entering and then remaining in a user created zone for a specified period.

People/Face Recognition

People and Face Recognition could easily be sliced into two core groups, but we keep them as one since they are so closely related. As Behavior Analytics need to detect human shapes to perform effectively, People/Face Recognition IVAs are next.

Human Detection

Image showing human detection video analytics from Gorilla Technology.

The Human Detection IVA detects human figures within the video. Once detected, features like clothing color, gender, eyewear, masks, and age group can be detected as well.

Face Recognition

Image showing face recognition video analytics from Gorilla Technology.

This IVA recognizes and identifies faces. This is used in conjunction with Gorilla's BAP software and its facial recognition database. While uses for this are myriad (and often in the news), we most often see Face Recognition used for Watch Lists, VIP identification, Attendance Systems, and Black Lists.

Vehicle Analysis

AI has been widely deployed by transportation authorities to keep traffic flow running smoothly, reduce traffic violations and aid with crime investigations. Edge computing generates real-time events and statistical data which can be used for timely decision-making and less workforce deployment.

Vehicle Classification


Detects vehicle types, e.g. motorbikes, cars and buses

Vehicle Direction Detection & Counting

Vehicle Direction Detection & Counting

Counts vehicles that move in a specific direction

Traffic Violation Detection


Recognizes the vehicles that violate traffic regulations or enter into prohibited areas

License Plate Recognition

Image showing license plate recognition video analytics from Gorilla Technology.

Recognizes license plates on static or moving vehicles

Image showing object recognition video analytics from Gorilla Technology.

Object Recognition

Replace the Face Recognition IVA with any given object and you'll get the Object Detection IVA. This is where algorithms are used in training the software to detect and recognize a specific object, like a hot dog. There are a lot of different objects in the world, so the training and size requirements add up quickly.

Business Intelligence

Dashboards in software showing data about various business activities are a valuable asset in just about any retail or enterprise setting. Using video analytics from within a dashboard to enrich and increase results should be a part in everyone's toolbox.

Image showing the dashboard user interface on Gorilla Technology's IVAR edge AI business intelligence video analytics solution.
Image showing the dashboard user interface on Gorilla Technology's Smart Attendance and Access Control business intelligence video analytics solution.
Image showing the dashboard user interface on Gorilla Technology's Smart Retail business intelligence video analytics solution.

While the IVAs in numbers one through four above are widely used for surveillance scenarios, there are magnitudes of business scenarios that can reap the benefits that video analytics offers. To see some examples, check out how Gorilla is applying these to create intelligent solutions for multiple business markets and industries.

Putting the Video Analytics Idea Together

As you read above, these IVAs all orchestrate various algorithms to achieve and deliver results. Essentially though, IVAs detect for and determine if a defined event or behavior has been found or occurs within a video camera's field of view and then notifies the designated user of the finding.

In a similar manner, most of us go through varying processes depending on if we're searching for keys at home or for our friend in a busy station.

Video Analytics Processing Power

Thinking about the entire process, could there be a single solution that can do everything effectively? It seems like an insurmountable amount of tasks: from processing each single frame's analytic data to displaying it together with the video, into creating a complete video system with an array of user selectable & customizable IVA in a building or any other scenario, all the way to putting multiple systems together that report back to a central control center.

It's not impossible. To demonstrate this, let's look at what IVAR™ from Gorilla can do and how it operates.

CPU and GPU Video Analytics Processing

Video analytics as a whole requires a lot of dedicated processing power. We should keep in mind here that before optimization and edge devices with capable CPUs, video analytics was processing both video and analytic data on one machine and required additional GPUs to do most of the work. Technology and the ability to split these two up has advanced to the point that it's now possible to keep the video data at the edge while pushing the analytic data up the network for quick processing.

One technology, which Gorilla was the first to adopt, is the Intel® distribution of the OpenVINO™ toolkit. Using the OpenVINO™ toolkit to optimize IVAR keeps deployment and upkeep costs low while decreasing operating temperatures by minimizing the need for expensive GPUs.

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