The CSI Effect: How TV is changing video surveillance

Futuristic shows have changed our expectations, but here's what you really need to know about CCTV today

"Greg, can you magnify the pixels in this video? I believe we may be able to ID the killer from that reflection in the victim's eyes."

That was Gil Grissom to Greg Sanders on CBS' CSI: Crime Scene Investigation.

The "CSI Effect," a very real phenomenon, is how the exaggerated portrayal of forensic science adversely affects jurors, criminals, and forensic science itself. Nested somewhere within forensic science now lies video surveillance, perceived as the magic bullet that solves hundreds of cases within minutes. By way of either mystical pixel magnification, or the likes of CBS' Criminal Minds' Penelope Garcia accessing any video system in the world and gathering the needed video within seconds, the recent portrayal of video surveillance has led to, in many cases, a very misinformed customer base with unrealistic expectations.

The CSI effect has also, in many ways, driven a change in our industry, as we see more movement from standard definition (SD) cameras, to megapixel (MP) and high definition (HD) cameras. The argument now rages on about what equipment to deploy so that you or your customer can be ready for that CSI moment.

In this article, we are going to look at a few of the factors in the deployment of video surveillance systems that affect the quality of video and the ability of the user to find the video or evidence they need. These fundamentals apply across the board no matter what video technology you are deploying.

Field of View
A camera's field of view (FOV) is determined by the angle of view from the lens to the scene and can be measured horizontally or vertically. The lens size (in millimeters), the type of lens, the size of the sensor inside the camera, and the distance from the camera to the target area are all factors that affect the field of view. Most manufacturers have online or handheld field of view calculators to assist with lens selection. Lenses play a key role in any application -- especially in HD and megapixel cameras. The basic equation for lens selection is as follows:

Lens (mm) = Distance (ft) / field of view (ft) x imager format (mm)

To determine the field of view (FOV) needed for an application, reference Johnson's Criteria. Johnson's Criteria was developed in 1958 and is currently used by the Army Night Vision & Electronic Sensors Directorate. It defines four levels of surveillance: Detection, Classification, Recognition and Identification.

This rule simply states the area of a scene, in percentage, that must be occupied by a person or object in order to be Detected (5% FOV), Classified (15% FOV), Recognized (50% FOV), and Identified (65%+ FOV). Although these numbers are based on night vision standards, the concept applies to all video surveillance applications.

For example, to read a license plate during daylight conditions, the rule is as follows: A 1 foot license plate must take up 10 to 15% of the horizontal field of view, depending on compression and resolution used (4CIF, H.263 or H.264).

Frames per Second (FPS) and Resolution
You pay for three things when you install a video surveillance system: inputs, storage and bandwidth. The most expensive portion of the system is the storage, and as I covered in an earlier article "Video and Data Are Not Created Equal," storage and bandwidth are joined at the hip. Frames per second settings are a pivotal part of any video surveillance system, and settings will vary from installation to installation based on the specifications and the type of facility. The first mistake usually made in specifications for a video surveillance system is reducing the frames per second and/or the resolution in an attempt to lower storage expenses.

Running at low frames per second at night coupled with higher frame rates on alarm can be beneficial if you are up against a "small storage, long retention time" scenario. But low frame rates become a problem when you are running at 1 to 10 frames per second all the time. In a high motion area with people and objects moving fast, you can miss important information (evidence) if you are only recording at 1 to 10 frames per second.

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