Page 40 - Security Today, November/December 2021

additional insights and recommendations, and draw on their support expertise during installation to help you optimize performance and ensure success.
FOLLOWING BEST PRACTICES
Many factors can influence the success or failure of analytics in an installation. Following best practices, however, helps avoid common pitfalls. It usually takes a bit of research to find out whether what you are trying to achieve is realistic. It helps to start with defining the operational requirements or purpose of the surveillance. After doing a site survey to scope out what is possible, what else might you consider when implementing video analytics? Here are a few examples:
People counter. A people counter analytic counts people passing through an entrance and in what direction they pass. The analytic can also estimate how many people are currently occupying an area and their average visiting time. In addition to following the camera’s installation, there are some recommended steps to take to ensure that the analytics behaves in expected ways.
• Install the camera at a minimum height per manufacturer’s recommendation.
• Mount it straight above the point where people pass.
• Avoid strong sunlight and sharp shadows in the camera view.
• Do not place cameras where moving objects such doors or escalators can interfere with the counting area.
License plate recognition. License plate recognition identifies the pixel patterns that make up a license plate and translates the letter, numbers and graphics on the plate and compares them in real-time to a database of plates. In selecting a good match for the location, it helps to know
the detection range and detection time of the camera. Some LPR cameras work well in traffic up to 45 mph. Others can handle vehicle speeds up to 90 mph, or faster.
Recommended camera adjustments.
Check the autofocus and manually fine- tune if needed. Turn off the wide dynamic range. Set the local contrast to a level that reduces noise at nighttime but keeps license plates visible. Set the shutter speed to maximum. Adjust the gain to optimize the blur and noise trade-off. Set the iris to automatic mode.
Recommended mounting. Avoid mounting the camera facing direct sunlight (sunrise and sunset) to prevent image distortion. Set the mounting angle at no more than 30o in any direction. The mounting height should be about half the distance of the distance between a vehicle and the camera.
Facial recognition. This is a category of biometric security. It is a way of identifying or confirming a person’s identity using their face from photos, videos or in real- time. Different operational goals effect the choice of lens, camera and field of view. Do you want to detect whether a person is present? Do you recognize that the person is the same as someone seen before?
Do you want to be able to identify the person beyond a reasonable doubt? Because real-life scenes tend to be complex, it is difficult, if not impossible to apply a single mathematical equation to determine the exact pixel density or resolution needed to meet these different operational objectives. The chart below, however, offers a general guideline.
Once you understand the operational requirements, you can use the number to identify the minimum resolution required and calculate the maximum width of the scene where the identification can occur.
Bear in mind that the lower the resolution, the narrower the maximum scene width. The operational requirements should also specifythecapturepoint,theimaginaryline across the camera’s field of view. Understand that the further back the capture line – placing the person further back in the image – the wider the capture line and the larger the identification area. However, the further away from the camera the person gets, the more the pixel density decreases.
Before the application goes live, it is best to use a pixel counter tool to validate whether the configuration choices you have made will meet the operation expectations of the customer.
WHAT THE FUTURE HOLDS
FOR ANALYTICS
Technology is evolving so quickly that if you can think it, eventually analytics will be able to do it. We are already seeing analytics detecting and evaluating ever more subtle nuances in behavior and environment, whether it is in the color and shape of people, vehicles, or objects, the way they move in a scene, or even how much heat they generate. We are seeing analytics applied to verifying compliance to health and safety standards, like wearing a hard hat in a construction site or a mask indoors during the COVID pandemic.
There are more analytics harnessing the power of machine and deep learning to predict performance and automatically trigger a range of responses to specific anomalies, such a redirecting traffic and changing the timing of traffic lights in real time to alleviate congestion.
Because of their ability for rapid discernment, we will likely see an increasing uptick in demand for use- specific applications. It will be up to trusted partners, security integrators, to stay abreast of what is feasible – learn to separate hype from reality. In that way, they can help their customers implement solutions that will actually meet their
expectations
Robert Muehlbauer is a senior manager of busi- ness development for Axis Communications.
Operational requirement
Horizontal pixels/Face
Pixels/cm
Pixels/inch
Identification (challenging conditions)
80 px/face
5 px/cm
12.5 px/in
Identification (good conditions)
40 px/face
2.5 px/cm
6.3 px/in
Recognition
20 px/face
1.25 px/cm
3.2 px/in
Detection
4 px/face
0.25 px/cm
0.6 px/in
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NOVEMBER/DECEMBER 2021 | SECURITY TODAY
ANALYTICS