System Design: 7 Deadly Surveillance Sins

While the average layperson can likely surmise a camera’s field of view, its apparent simplicity can be deceptive. This is particularly true where it comes to designing security surveillance systems. Learn how to avoid common mistakes associated with camera layouts, lighting and pixel dilution.

For nighttime coverage, the camera field of view should align with the field of view of the infrared illuminator. In this illustration, you can see how camera FOVs and illuminator FOVs need to be adjusted to align.4. Only Thinking About the Camera

By the very definition of field of view that we explored in the first paragraph, it would seem odd to think about anything other than the camera. But in fact, one major mistake in setting up a camera’s FOV is not considering the FOV of the illuminant. Whether you are using IR illumination, or even white light illumination, for nighttime monitoring the most important aspect is not the FOV of the camera, but rather the FOV of the IR illuminator or visible light source.

If you have ever viewed a camera at night with little or no illumination then you understand why this is important, you basically get a black video feed. If you want your nighttime FOV to correspond with your daylight FOV, then you need to ensure that your illuminator beam matches your camera FOV in both distance and width. Some illuminators have adjustments where you can make the beam narrow and long, or wide and short. Others have a fixed light pattern. In almost all cases, the resulting FOV that matches the illuminator’s capability will be a substantially shorter distance than what can be achieved with the camera alone in full daylight conditions.

Not taking the FOV of your illuminant into consideration can be a costly mistake in terms of coverage. You’ll need to stay up late to ensure these coverages match, but make sure you also consider the FOV
of your illuminant during the planning phases, or you could end up with gaps in your nighttime coverage.

5. Not Understanding Pixel DilutionThe “rule of thirds” applies when you are taking vacation photographs, but it does not apply when aligning security cameras. Plan to only allow 10% of the view to be above the horizon line.

Pixel dilution is the idea that the more information that is attempted to be represented by an individual pixel, the more diluted that information becomes. This issue typically arises when setting up a scene and opening up the camera’s FOV so it is as wide as can be accommodated by the lens. It’s available information, so why shouldn’t we widen the lens to capture it? The answer is … it depends. 

The important concept to understand is a camera is designed to give you a certain number of pixels, which is effectively video information. Changing the lens or the zoom level of a lens gives you a different FOV, but it does not give you any more pixels. The pixels are constant. So widening the scene effectively dilutes the video information of any particular pixel.

Here is one way to conceptualize it: Consider the number of pixels you have with a given camera as a cargo net made of elastic. Each square in the net represents a pixel. If you widen the view of the camera, you effectively stretch the net. You have widened the pixels, but remember a pixel is only a single value, so now you’ve stretched that single value over more of your scene. In practical terms, that means you will have less information about a specific object at a given distance.

As an example, a narrow FOV may give you enough pixel information to allow you to read a person’s baseball cap at 100m, while a wide FOV of that same person may not contain enough information in the diluted pixels to be able to determine if the person is even wearing a hat. So it is a planning decision to determine whether it is more important to view a wider area at the expense of more detailed video information, or to restrict the size of the FOV and gain that data. The mistake is not understanding the tradeoff being made.

6. Getting an Interesting View

We all like to be entertained, but that isn’t necessarily the best approach when setting the FOV of a security camera. A common mistake is to include “interesting areas” in the FOV, versus areas of interest.

A wide field of view will dilute the available pixels, causing a loss in information about a specific target, as shown in this example with the same target viewed at 50m with two different FOVs (4CIF, 480 X 320). To preserve the maximum amount of pixel information, the width of the FOV should be no wider than what is required to effectively monitor the scene.For example, consider a situation where a high traffic sidewalk runs next to a facility’s perimeter fence. Oftentimes the camera’s FOV is set to include this high traffic region. However, if the area of interest is not the sidewalk itself, but rather the region between the sidewalk and the fence, the argument is why the sidewalk would be included in the camera’s FOV. Every movement on the sidewalk now becomes the responsibility of the monitoring guard or security software to detect and assess as a possible threat. The same can be said of roads or areas of water that occur in the background. If the area is not of interest from a security standpoint, then care should be taken to consider whether the FOV should include the region. 

7. Not Understanding Camera Mission

A final aspect of the FOV is understanding the intended mission of the camera. In practice this rarely goes beyond the setup of the detection area. However, as cameras become higher in resolution, there are more missions to consider.

For detection, it is typically better to have a FOV that is taken from a higher vantage point. This helps avoid occlusions, allows for better understanding of the target’s current track and potential trajectory. However, a higher vantage FOV is not always conducive to facial or clothing identification, where the face or clothing graphics are seen as at an angle, or blocked by a hat. The opposite holds true, where a lower FOV results in better identification, but potentially poorer tracking and detection. Again, the mistake is not whether to have a high FOV or low FOV, it is not understanding the benefits and drawback of each, and not using the camera’s mission to drive the most appropriate height when setting the FOV.

Eric Olson is Vice President of Marketing at Phoenix-based video analytics developer PureTech Systems.

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