With any major technology shift, there are often discrepancies between what the public imagines and what is practical.

Facial recognition, for example, had people trying to find faces in a crowd from a watch list shortly after 9/11, which was completely beyond its capability at the time. The technologists knew this, but some companies still encouraged projects like this, creating a serious negative reaction.

We’ve seen disappointment in some applications with video analytics, such as baggage left behind detection in an airport, which is far more complicated to make work practically than is generally presented. We at VideoIQ have avoided even offering it for this reason.

This makes education important. The good news is that most in the industry are trying to set better expectations on what is realistic.

However, there is one area that is shockingly out of whack.

Of the five largest camera companies in the security industry – all well known names by any integrator – except for Axis, they all claim to offer Video Analytics options with some of their IP cameras.

Most people assume this means that they are offering the kind of detection and performance as the largest and most well established names in the Video Analytics space. Technologies like VideoIQ and other early entrants were, after all, the ones who established what Video Analytics means to the industry. However, the software these camera companies provide and the advertisements they run suggest that they have the same capabilities. It is one of the biggest lies I’ve seen in the industry for a long time.

I can certainly see why they would want customers to believe they are offering products in the same class, but the technology isn’t even close. And it is clear that they know it, since they not only use the term Video Analytics when referring to their technology, they also call it Intelligent Video Motion Detection, or Adaptive Motion Behavior, or Motion Detection, etc.

What they are really offering is what is known as Advanced Video Motion Detection, and this is dramatically different from true Video Analytics.

For example, none of these AVMD technologies can distinguish a human or a vehicle from anything else, except by size. In other words, they only recognize a blob of moving pixels, and if the size of that blob is about right then and only then will it be detected. This falls far short of true object type detection.

Secondly, these technologies cannot work accurately in scenes with highly dynamic backgrounds, such as blowing bushes or tree branches, or rippling water: In other words, the types of changes and movements you find in typical outdoor applications.

You have to dig deep into their manuals to find the truth. Here are warnings from one of the big five:

  • Movements may falsely be detected if there is: a reflective metal background, glass (glazed building frontages), water as a background
  • Large areas of reflected light can also cause spurious motion detection
  • A constant background is necessary in order to detect motion reliably
  • A person walking front of a hedge that is moving in the wind will very probably not be detected

Another of the companies added these warnings:

  • The ideal scene selection is one with light traffic and a clean background
  • If heavy traffic or a busy background is unavoidable, place the monitoring zone or trip wire in a relatively stable area
  • Avoid crowded scenes where people move in all directions or stand in one place for long periods of time

One of the top camera companies offered no warnings at all. However, the largest camera company in the industry gave the best list to show the limitations of Advanced Video Motion Detection. They say their technology might not work if the:

  • Camera is shaking.
  • Depth of object is too long.
  • Object is too big or too small.
  • Fluorescent light is flickering.
  • Too many objects are moving.
  • Weather condition is extremely poor.
  • Movement of object is too fast or too slow.
  • Object is moving directly toward the camera.
  • Dirt, drip, or splash is on the dome cover of camera.
  • Luminance level of image is too low (During nighttime, etc.)
  • Outside light (sunlight, headlights, etc.) enters the shooting area.
  • Luminance level of shooting area is subject to change (outdoors, by the window, etc.)

Real Video Analytics technologies can work under all of the conditions listed above. There are of course limits, and there are still false alarms, but you will see about 10X – 100X times as many false alarms in typical outdoor environments with AVMD, and many times more missed detections as well.

Advanced Video Analytics systems are designed to:

  • Detect colors, contours, shapes and movements of humans and vehicles, not just luminance levels
  • To ignore fluorescent lights flickering, sunlight, headlights
  • Work in bad weather: Rain, snow, hail, sleet, fog
  • Ignore camera shaking, dirt and drips on dome or lens
  • Adapt to changes in environment automatically

If used indoors away from windows, a good AVMD system should work fine. Motion detection has always been usable indoors, and the new Advanced Motion Detection systems are slightly better. However, outdoors is another story.

These companies should be up front about these limitations, and they should be making it absolutely clear that AVMD is not in the same league as the technologies from VideoIQ and other true Video Analytics providers.

The problem with all of this is that the term, Video Analytics, is not being used carefully. People are using it to describe everything and anything, including traditional motion detection, license plate recognition and facial recognition. My suggestion is that industry start clearly differentiating: The term Video Analytics should only be applied if the system can provide:

  1. True object type recognition, not just pixel blob detection
  2. Able to discriminate objects of interest from highly dynamic background movement
  3. Automatically adjusts to changes in the environment
  4. Can track objects through the field of view

If it can’t do all of these, then it should be called AVMD.

The terms, License Plate Recognition (LPR) and Facial Recognition (FR) are clearly recognizable. There is no need to lump these into the term, Video Analytics. It only confuses what Video Analytics stands for, and leaves us with no clear way of distinguishing the type of system described above. Clarity is important, and so is honesty.

What is fascinating about this lie is that it isn’t the Video Analtyics companies who are perpetuating it. Usually you find the start-up companies with the breakthrough technology who get carried away, hoping for more attention. But in this case, the biggest camera companies in the industry (except for Axis) are the ones trying to ride on the coattails of the Video Analytics leap forward.

There is no excuse for not making these differences clear, and no one should be trying to make it look as if they are selling Video Analytics when they aren’t.