Optimising SecuritySpy’s AI Object Detection

The new AI-powered motion detection features in SecuritySpy version 5 use deep neural networks to detect the presence of humans and vehicles. This allows for highly-accurate triggering of recordings and notifications of just the events that you are interested in.

The AI algorithms output a prediction probability, indicating the likelihood for the presence of a human or vehicle, and you can choose the threshold at which this triggers recording and notifications. Generally, a threshold of around 85% gives good results.

However, the accuracy of the AI depends on many factors such as the distance to the subject, lighting, resolution and quality of the camera. You might find that a threshold of 85% is letting through too many false-positive triggers, or conversely is preventing real motion from generating a trigger.

To see how the AI is performing on your system, create a folder called “AI Predictions” in the SecuritySpy folder within your Home folder (to get to the Home folder, click the Go menu in the Finder and select Home). Then, whenever a video frame is passed through the AI, SecuritySpy will annotate the frame with the motion area and prediction probabilities, and will save it to this folder as an image file. Inspecting these images allows you to determine what the AI is “seeing”, and will therefore allow you to adjust your trigger thresholds for optimum results on your system.

Here are some examples of these annotated images (cropped to just the relevant area):



A high-quality setup with a high-resolution camera and good lighting is likely to result in highly accurate predictions that are close to 100%. In this case, you might like to increase the threshold value (perhaps to 90%) in order to to cut out more false-positive detections. Conversely, if the image quality is not so good, the AI predictions are likely to be less certain, and you probably want to reduce the trigger threshold to make sure that you don’t miss any real motion.

Note that in general, the AI algorithms work best with high-quality cameras. If you are using low-quality cameras, or your cameras are frequently operating in low lighting conditions and producing grainy/noisy images, it may be best to disable the AI and stick to standard motion detection.

Minimising CPU Usage

Initially, standard motion detection is performed on the incoming video stream to determine which frames to pass to the AI for further analysis. Because the AI can consume significant CPU resources, it is important to use suitable settings for this first-stage motion detection. Generally, this means using a sensitivity setting of 50-60% and a trigger time setting of at least 1 second.


Exactly how much CPU time is used depends on the speed of your Mac and whether it supports GPU-based hardware acceleration. Without hardware acceleration, analysing one video frame via the AI results in very high CPU usage for a very short period of time (e.g. 50-100ms).

4 thoughts on “Optimising SecuritySpy’s AI Object Detection

  1. Nan

    I am trialing the new software, you mention above GPU based hardware acceleration. I’m not a computer expert. I am running SS on a 2019 IMac 27″ 5k retina. Does it have the hardware to run this sofware properly. I ask as I have had several warnings about high CPU use since installing the trial version 3 weeks ago. Thanks!

    1. Ben Software Post author

      Yes, your iMac is suitable for running SecuritySpy. If you are getting warnings about high CPU usage, this can be resolved with some settings tweaks. The main thing to check is the frame rates (fps) that your cameras are set to, as unnecessarily high frame rates can lead to high CPU usage. Connect to each of your cameras using a web browser to check their settings and adjust the frame rate of video that they are sending – I suggest that 10fps is good for general-purpose CCTV. We also have some further recommendations in the Optimising Performance section of the user manual.

    1. Ben Software Post author

      Not at the moment, but we are working on this feature and it will be available in a near-future version of SecuritySpy.


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