# Use thermal cameras to detect, then visual cameras to identify > Thermal cameras can reveal people and vehicles through darkness and difficult backgrounds, but thermal imagery generally cannot identify a person. Design detection, visual verification, analytics, and response as separate tested functions. - Canonical URL: https://update.dsesecurity.com/updates/pair-thermal-detection-with-visual-verification/ - Publisher: Detection Systems & Engineering (DSE Security) - Author: Robert Dix - Published: 2026-08-11T10:20:00+00:00 - Modified: 2026-08-11T14:48:23+00:00 - Last reviewed by DSE: 2026-08-11 - Resource type: Guide - DSE priority: Advisory - Topics: Video Surveillance - Reading time: 3 minutes ## What you need to know Thermal cameras can reveal people and vehicles through darkness and difficult backgrounds, but thermal imagery generally cannot identify a person. Design detection, visual verification, analytics, and response as separate tested functions. ## Potentially affected Perimeters, yards, parking areas, substations, industrial sites, campuses, critical facilities, and other locations considering thermal cameras or thermal video analytics. ## DSE recommendation Define the thermal detection target and range, validate it through representative weather and seasonal contrast, and pair every actionable alarm with a tested visual-verification and response path. ## Article ## Source facts: thermal and visual cameras answer different questions Axis Communications’ white paper, [Thermal cameras](https://whitepapers.axis.com/en-us/thermal-cameras), explains that thermal sensors create images from infrared radiation emitted by objects as a function of temperature. They do not depend on visible illumination. Small temperature differences can make a person or vehicle stand out against darkness, shadows, camouflage, or a visually complex background. That strength is primarily detection and shape recognition. Axis states that thermal images alone are generally insufficient to identify a specific person. In an integrated perimeter workflow, a thermal camera can detect an intruder and direct a visual camera toward the event so an operator can verify and, where the installed view supports it, identify the subject. Thermal performance should not be reduced to a single attractive range figure. Focal length, sensor resolution, target dimensions, required task, temperature difference, analytics requirements, and environment all matter. Axis discusses Johnson’s criteria as a planning method and notes that analytics may require more pixels than the human-observer rules of thumb. ## Source facts: weather and thermal contrast still affect range Thermal imaging often performs better than visual imaging in darkness, moderate fog, smoke, or difficult lighting, but it is not weather-proof vision. Rain, fog, and smog attenuate thermal radiation and reduce detection range. Weather and solar heating can also make target and background temperatures more alike. The source’s planning examples assume a temperature difference; actual site performance can differ. Noise equivalent temperature difference, or NETD, describes a sensor’s ability to distinguish small thermal differences, with a lower value generally indicating better sensitivity. Axis cautions against rating cameras only by NETD because measurement methods are not standardized sufficiently for simple cross-product comparison. Complete camera processing and the real scene affect the delivered image. ## DSE recommendation: assign one job to each sensing layer Write the thermal requirement as a detection statement: target class, minimum size, direction, speed, near and far boundaries, environmental range, alarm zones, and maximum acceptable nuisance rate. Separately define what the visual camera must provide after an alarm—overview, recognition, identification, color, clothing detail, plate capture, or simply confirmation that a person is present. Do not imply that a long thermal detection range is also an identification range. Show both boundaries on the site plan. If the visual camera cannot cover the thermal alarm area with the required detail and lighting, the response chain has an evidence gap. ## DSE recommendation: commission the difficult conditions - Walk every boundary. Use authorized people and representative vehicles at the near edge, far edge, corners, approaches, and partial-obstruction points of each zone. - Vary target behavior. Test walking, running, stopping, crouching where relevant, movement toward and across the camera, and more than one object. - Challenge thermal contrast. Repeat during warm and cold periods, after sun-heated surfaces begin cooling, in rain or mist when practical, and against backgrounds relevant to the site. - Validate the analytic. Record detection probability and nuisance sources such as animals, exhaust, moving vegetation, reflections from heated surfaces, or permitted traffic. Tune zones and classifications from evidence. - Prove visual handoff. Confirm that the correct visible-light camera, preset, live view, recording, bookmark, and operator instruction arrive in time to support the response. - Test degraded states. Disconnect or obstruct each camera in a controlled test and verify that monitoring reports the loss rather than silently leaving an unverified alarm path. ## DSE recommendation: retain role-specific acceptance evidence Keep a thermal clip and corresponding visual clip for each critical test point, along with lens, firmware, analytic version, palette, zone, time, weather, target, result, and reviewer. Record the longest verified detection distance, not merely the manufacturer’s calculated maximum. Revalidate after foliage changes, construction, new fencing, camera movement, lens or firmware changes, analytic updates, or repeated nuisance alarms. The successful system is not a thermal camera with an impressive picture. It is a measured detection layer connected to visual verification and a response procedure that operators have demonstrated under realistic conditions. ## Official references - Axis Communications, [Thermal cameras](https://whitepapers.axis.com/en-us/thermal-cameras), October 2021. ## Primary reference - Name: Axis Communications: Thermal cameras - Authority: Axis Communications - URL: https://whitepapers.axis.com/en-us/thermal-cameras - Source publication date: 2021-10-01 ## Citation and use Preferred citation: “Use thermal cameras to detect, then visual cameras to identify,” DSE Security, https://update.dsesecurity.com/updates/pair-thermal-detection-with-visual-verification/ Publishing principles: https://update.dsesecurity.com/updates/dse-updates-editorial-methodology/ Usage and citation policy: https://update.dsesecurity.com/usage/ Copyright © 2026 Detection Systems & Engineering. All rights reserved.