In recent years, many security systems have started using artificial intelligence (AI) to automatically detect people in the camera footage. This technology allows CCTV cameras to identify humans in real-time, without the need for human intervention. However, one crucial factor that can impact the accuracy of AI human detection is lighting.

What is AI Human Detection?

AI human detection uses machine learning algorithms to recognize human shapes, movements, and features like faces or bodies in video footage. This technology enables security cameras to automatically identify when a person is in view, triggering alerts or taking action as needed.

How Does Lighting Affect AI Human Detection?

Lighting plays a big role in how well AI can detect people in a scene. Here’s why:

  1. Too Little Light (Low Lighting)
    If there isn’t enough light, the camera may struggle to capture clear images. The AI may not be able to distinguish people from the background, or it might miss key features like faces or body parts. In low light, humans can appear blurry or indistinct, which reduces the AI’s ability to detect them accurately.

  2. Too Much Light (Overexposure)
    On the other hand, if there is too much light, such as bright sunlight or direct artificial light (like floodlights), parts of the image can become "washed out." When this happens, the camera’s sensor might not be able to properly capture the details of the scene, causing the AI to miss important features like facial details or body shapes.

  3. Harsh Shadows and Glaring Light
    Sometimes, lighting creates harsh shadows or bright glares that confuse the camera. For example, if someone stands in front of a window with sunlight pouring in, their face may be in shadow or the entire figure may appear too dark. In this case, AI might fail to recognize the person entirely or only detect part of them, like a silhouette.

  4. Changing Light Conditions
    Lighting can change throughout the day or due to factors like turning lights on and off. For example, during dusk or dawn, when natural light fades or fluctuates, AI detection systems can struggle to adjust quickly, leading to missed detections or incorrect identification.

Why Does This Matter?

The goal of AI-powered CCTV systems is to detect and track people accurately in real-time, regardless of changing light conditions. If the lighting isn't ideal, the AI might:

  • Miss detecting a person entirely, especially in low-light situations.
  • Incorrectly detect a person in cases where shadows, glare, or overexposure confuse the system.
  • Trigger false alarms, thinking there is a person when there isn’t, or failing to recognize someone important.

How Can You Improve AI Human Detection in CCTV?

Here are a few ways to improve AI detection in various lighting conditions:

  1. Use Cameras with Better Low-Light Performance
    Some modern cameras are designed to work well in low-light settings. These cameras use advanced sensors to capture clearer images even when there isn't much light, making it easier for the AI to detect people in the scene.

  2. Add More Light
    In darker areas, adding extra lighting—such as motion-activated lights—can improve detection. However, be careful not to add too much light, as this can cause overexposure and reduce the effectiveness of AI detection.

  3. Use Smart Lighting
    Some CCTV systems come with smart lighting features that automatically adjust brightness depending on the time of day or the amount of natural light. This ensures a balanced level of light throughout the day, improving the clarity of the footage.

  4. Adjust Camera Angles and Placement
    Positioning cameras to avoid direct sunlight or intense artificial lighting helps reduce glare and shadows. Proper camera placement ensures the best possible image quality for accurate AI detection.

  5. Ensure the correct camera is used for the application

    Selecting the right camera is crucial to ensuring that there is sufficient light across the entire area covered by the camera's view. For nighttime or low-light conditions, Infrared (IR) illumination is often the best option. IR cameras use infrared light to capture clear images in the dark without relying on visible light, making them ideal for night-time surveillance.

    Colour cameras, on the other hand, may struggle in low-light environments. While they can provide full-color images during the day, they often introduce undesirable artifacts (such as noise or graininess) and motion blur when used in low-light or nighttime conditions. These issues can interfere with the AI's ability to accurately detect and track human movements, leading to missed detections or false positives. For this reason, IR cameras are generally preferred for AI-powered human detection at night.

In conclusion, lighting plays a critical role in the effectiveness of AI human detection systems in CCTV cameras. Poor lighting can reduce the system’s accuracy, leading to missed detections or false alarms. By optimizing lighting conditions and using the right technology, you can improve the performance of AI-based surveillance systems and enhance security.