Video Analytics & AI Monitoring Flashcards

Which video analytics technique is most effective for detecting loitering in a defined zone?

Answer: Dwell-time analysis

Dwell-time analysis tracks how long an object remains within a defined region of interest and triggers alerts when the threshold is exceeded.

In AI-based video surveillance, a high false-positive rate primarily indicates which issue?

Answer: Poor model precision

A high false-positive rate reflects low precision, meaning the model incorrectly flags non-events as security incidents too often.

What is the primary purpose of a 'virtual tripwire' in video analytics?

Answer: Triggering alerts when objects cross a defined line

A virtual tripwire is a configurable line in the video frame that triggers an alert whenever an object crosses it in a specified direction.

Which AI model architecture is most commonly used for real-time object detection in surveillance systems?

Answer: Convolutional Neural Network (CNN)

CNNs excel at image feature extraction and are the foundation of most real-time object detection frameworks like YOLO and SSD used in surveillance.

When deploying edge-based video analytics, what is the primary advantage over cloud-only processing?

Answer: Reduced latency and bandwidth consumption

Edge processing analyzes video locally on the device, reducing the need to transmit large video streams to the cloud and enabling near-real-time alerts.

A surveillance AI system has 90% recall. What does this metric indicate?

Answer: 10% of actual events are missed by the system

Recall (sensitivity) of 90% means the system correctly detects 90% of actual events, but misses 10% of real incidents (false negatives).

Which privacy-preserving technique allows video analytics to detect people without retaining identifiable facial images?

Answer: Silhouette-based detection

Silhouette-based or skeleton detection extracts body shape and movement without capturing facial features, protecting individual privacy.