How does AI handle occlusions, such as an object blocking the camera’s view?

AI handles occlusions—such as an object blocking the camera’s view—by using various techniques within video analytics and artificial intelligence. Here’s how AI-based video monitoring systems mitigate occlusion challenges:

Object Persistence and Tracking: AI-based video analytics use object tracking algorithms to predict and maintain the location of partially or temporarily occluded objects. By analysing an object’s movement before and after occlusion, AI can infer its probable position even when not fully visible.

Multi-Camera Integration: Many AI video monitoring systems support multiple camera views. If an object is occluded in one camera, another camera from a different angle may still capture it, helping maintain situational awareness.

Scene Context and Predictive Modeling: AI models analyse the historical and environmental context, allowing them to anticipate where an occluded object is likely to reappear. This is especially useful in perimeter protection and behavioural analytics.

Edge and Cloud-Based AI Processing: AI systems use advanced edge computing and cloud-based processing to continuously refine detection accuracy, reducing false alarms and improving object classification even when partial occlusions occur.

Adaptive AI Learning: Continuous AI training ensures the system adapts to scenarios where occlusions frequently occur, such as people walking behind parked cars or moving objects in a cluttered environment.

Noise-Cancelling and Scene Filtering: AI algorithms apply noise filtering techniques to enhance detection accuracy by distinguishing relevant and irrelevant movements. This is useful for reducing false alarms caused by temporary obstructions like foliage or reflections.

AI-Powered Anomaly Detection: Some AI video analytics platforms, like those used in false alarm filtering, detect anomalies by comparing current video feed data with baseline scene models. This helps identify partially hidden objects by analysing their behaviour over time.

While AI is highly advanced, complete occlusions can still pose challenges. However, AI-based systems leverage redundancy across multiple data points to ensure that security and surveillance operations remain effective.