Campus protection professionals have their hands full like never before. Not only do they need to understand how bad guys think, they also need to understand the vast number of security products and feature sets designed to aid them in securing their facilities.

Many times, a single product feature or capability in itself can be confusing and sometimes misleading. One such example is camera auto follow, the powerful perimeter protection technique that provides the ability to track an intrusion hands-free. If you Google the most popular search terms relating to the concept of camera auto follow you will get a host of options, including: pan/tilt/zoom follow, p/t/z auto follow, p/t/z following, camera auto tracking, auto tracking camera, motion tracking camera and so on.

So the question becomes what are all these different variants and how does one go about asking the right questions to know what flavor you are getting? Read on to learn about such variables as application definitions; camera controls; single vs. multicamera deployment; detection types; and invoking methods.

Why Camera Auto Follow Can Be a Force Multiplier
Let’s begin with what camera auto follow is not. Many terms can refer to an entirely different set of functionalities. Oftentimes the word “motion” or “tracking” refers to the device’s ability to detect video motion but not physically move the camera to track an object.

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This brings up an entirely new set of questions relating to the types of objects it can detect (pixel-based, classification, tracking) and how this detection is achieved (learning vs. rules-based). This type of detection is very beneficial for the protection of critical assets, but for the purpose of this discussion we are referring to functionality that involves automatic control of the camera movement.

So what is camera auto follow? A simple definition is the capability to automatically control a p/t/z camera’s pan, tilt or zoom in an attempt to keep a specified object centered in the camera’s field of view (FOV). This is typically achieved via a closed loop control algorithm that continually identifies the target, its current position in the camera’s FOV and its trajectory.

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