{"id":82620,"date":"2026-09-23T14:36:25","date_gmt":"2026-09-23T17:36:25","guid":{"rendered":"https:\/\/a3aengenharia.com\/?post_type=articles&p=82620"},"modified":"2026-09-23T14:36:25","modified_gmt":"2026-09-23T17:36:25","slug":"pixel-density-video-surveillance-calculate-px-m-field-of-view","status":"publish","type":"articles","link":"https:\/\/a3aengenharia.com\/en-us\/content\/technical-articles\/pixel-density-video-surveillance-calculate-px-m-field-of-view\/","title":{"rendered":"Pixel Density in Video Surveillance: How to Calculate px\/m and Size the Field of View"},"content":{"rendered":"\n

The pixel density in video surveillance<\/strong> indicates how many image pixels represent one unit of scene width at the target plane, normally expressed in pixels per meter (px\/m)<\/strong>. The basic calculation is straightforward: divide the horizontal resolution actually used by the horizontal scene width, in meters, in the region where the requirement must be met. Thus, an image with 1920 horizontal pixels distributed across an 8 m width produces, on average, 240 px\/m<\/strong> at that plane.<\/p>\n\n\n\n

The number, however, should not be treated as a fixed property of the camera. Density changes with distance, focal length, field of view, stream resolution, cropping, dewarping, and scene geometry. Even when the calculated value is sufficient, lighting, movement, shutter speed, compression, noise, focus, and target angle can reduce the detail that is actually usable. Therefore, px\/m is a design and verification criterion<\/strong>, not a substitute for image testing.<\/p>\n\n\n\n

The standards reference also needs to be updated. The IEC 62676-4:2025<\/strong>, second edition, replaced the 2014 edition and redefined the pixel-density system. The classic levels associated with DORI remain relevant for understanding legacy designs, datasheets, and installations, but they should not be presented as if they were the current classification in the 2025 international edition. This article separates these two layers and shows how to calculate, specify, and validate pixel density without turning the standard into a decontextualized table.<\/p>\n\n\n\n\n

What Is Pixel Density in Video Surveillance?<\/h2>\n\n\n\n

Pixel density is the relationship between the number of pixels available in the image and the physical dimension of the scene those pixels represent in a region of interest. In video surveillance, the most practical unit is px\/m<\/strong>.<\/p>\n\n\n\n

The concept can be written as:<\/p>\n\n\n\n

pixel density (px\/m) = useful horizontal pixels \u00f7 scene width at the target plane (m)<\/code><\/p>\n\n\n\n

If a stream has 3840 horizontal pixels and the observed region is 12 m wide at the analyzed plane:<\/p>\n\n\n\n

3840 \u00f7 12 = 320 px\/m<\/code><\/p>\n\n\n\n

This means that, under that geometric condition, each meter of scene width is represented by about 320 horizontal pixels.<\/p>\n\n\n\n

The term useful pixels<\/strong> is important. The calculation should consider the image resolution actually used for the operational task \u2014 viewing, recording, export, or analysis \u2014 and not necessarily the sensor’s nominal megapixel count. If a high-resolution camera records a reduced secondary stream, the resolution of that stream limits the detail available in the recording.<\/p>\n\n\n\n

The specification of video-surveillance monitoring points<\/a> addresses the complete functional unit of the design. Pixel density is one of the parameters of that specification, alongside operational objective, region of interest, lighting, geometry, movement, and test criterion.<\/p>\n\n\n\n\n

Why Megapixels Alone Do Not Determine Whether a Camera Meets the Requirement<\/h2>\n\n\n\n

Saying that a camera has 2 MP, 4 MP, 8 MP, or 12 MP does not indicate how much detail will reach the target. Total sensor resolution is only one variable in the relationship.<\/p>\n\n\n\n

A camera with many pixels can deliver low density when it uses a very wide field of view. Likewise, a lower-resolution camera can provide high density when observing a narrow passage, a doorway, or another target framed in a controlled manner.<\/p>\n\n\n\n

Consider two situations with 1920 horizontal pixels:<\/p>\n\n\n\n

Scene width<\/td>Horizontal resolution<\/td>Average density<\/td><\/tr>
4 m<\/td>1920 px<\/td>480 px\/m<\/td><\/tr>
8 m<\/td>1920 px<\/td>240 px\/m<\/td><\/tr>
16 m<\/td>1920 px<\/td>120 px\/m<\/td><\/tr>
32 m<\/td>1920 px<\/td>60 px\/m<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

The camera is the same. What changes is how much of the scene each pixel needs to represent.<\/p>\n\n\n\n

This shows why specifications such as \u201cminimum 4 MP camera\u201d are incomplete when the objective is image performance. The requirement should begin with the information that needs to be obtained from the scene and only then be converted into resolution, lens, distance, position, and other characteristics.<\/p>\n\n\n\n\n

From Camera Resolution to Pixel Density at the Target<\/h2>\n\n\n\n

The design chain can be summarized as follows:<\/p>\n\n\n\n

Relationship between Operational Requirement, Geometry, and Pixel Density in a Video-Surveillance Design<\/title>