Video Analytics Versus Behavioral Video Analytics – What’s the Difference?
Video analytics is a hugely powerful tool for security professionals. It allows you to enhance your understanding of recorded data without having to manually sift through hours of footage, which leaves you susceptible to human error and exhaustion.
What is Video Analytics?
In its simplest form, “video analytics is a technology that leverages existing video surveillance networks to derive searchable, actionable, and quantifiable intelligence from live or recorded video content.” (1)
It uses existing visual data streamed from network cameras to perform real-time detection and post-event analysis of multiple image scenarios. In 2022, it has advanced to incorporate artificial intelligence (AI) to identify trends in video data, and objects of interest as trained by machine learning, and even compile analyses into visual reports to help you leverage the contents of your video surveillance systems most effectively.
Applications you may be familiar with include heat mapping, people/ head counting, and facial recognition.
What is Behavioral Analytics?
Behavior detection or behavioral video analytics allows computers to automatically detect things of interest – according to certain predefined parameters – without the need for any human viewing of the footage. It can also flag singular images, or contextual video feeds, which present markers indicative of suspicious behavior/ unattended objects. It tends to be what people mean when they talk about AI-powered video analysis.
Owing to its increased accuracy and better contextual understanding, behavioral video analytics can be crucial in settings such as banks, perimeter intrusion monitors, stadiums, airports, public transport, parking, and vehicle monitoring. (2)
The importance of behavioral video analytics in high-profile or high-risk settings is therefore clear. It reduces the number of people needed to monitor video streams and can also help prevent crimes from happening rather than just facilitating a fast response post-event.
Types of Behavioral Analytics
Behavioral video analytics comes in two main forms – fixed algorithm analytics and AI analytics – and both are used to detect suspicious behavior and alert relevant security teams as soon as possible. (3)
Fixed algorithm analytics look for specific behaviors, according to what markers you input. They are great for catching specific behaviors which could go unnoticed when monitoring multiple video streams, and where suspicious behavior follows a somewhat predictable format. For example, spotting objects which have been left unattended for x amount of time, someone going the wrong way in a crowd, or unexplained loitering.
AI analytics use machine learning to learn from past video streams, and to form predictive analyses which improve with more data. Once implemented, AI video analytics uses the first few weeks to determine what is considered ‘normal’, and can then compare future visual data to its stored memories to distinguish problematic behaviors. Rather than looking for certain criteria like fixed algorithm analytics, AI analytics is better used in cases where suspicious behavior doesn’t necessarily follow a set pattern but instead follows no pattern.
Video vs. Behavioral Video Analytics
There doesn’t appear to be any logic behind not using behavioral video analytics if it is indeed an option for you, be that fixed algorithm or AI.
It improves on the benefits offered by standard video analytics by:
- Preventing crime using AI and constant learning
- Detecting suspicions from single static images, meaning faster identification and reporting
- Using AI to allow for better contextual awareness and thus higher accuracy
Therefore, enhanced by AI, algorithmic parameters, deep learning and machine learning, behavioral video analytics could be a game changer when it comes to improving situational awareness, combining the most cutting-edge technologies to significantly improve your security practices.
Ask An Expert
The CGL Electronic Security Team of security professionals is available to help you make the right choice to maximize your video analytic goals and objectives.
To learn more, visit the CGL website or contact me at email@example.com.
Mike McGuirk, Vice President of Sales, CGL Electronic Security