Media Server 24.1

# Persistent Change Detection

Detects moving objects and generates an alert when an object becomes stationary and remains stationary, causing a change in the scene. You can use this engine to detect dropped or abandoned bags. This engine requires video input (images are not supported).

Configuration Parameter | Description
--- | ---
FreeformRegion | The region of the scene that you want to monitor.
Input | The name of the image track to analyze.
MaxSize | The maximum expected size of an object.
MinimumTime | The minimum amount of time that an object must remain stationary.
MinSize | The minimum expected size of an object.
NumParallel | The maximum number of video frames to analyze simultaneously.
Region | The region of the scene that you want to monitor.
SampleInterval | The interval at which frames are selected to be analyzed.
Type | The analysis engine to use. Set this parameter to `PersistentChangeDetection`.

## Output Tracks

Output track | Description
--- | ---
`Data` | Contains one record for each object that is stationary for longer than MinimumTime, for each video frame.
`Result` | Contains one record for each object that is stationary for longer than MinimumTime.
`ResultWithSource` | The same as the `Result` track, but each record also includes the best source frame.
`Start` | The same as the `Data` track, except it contains only the first record of each event.
`End` | The same as the `Data` track, except it contains only the last record of each event.
`Alert` | Contains one record for each object that is stationary for longer than MinimumTime. This track differs from the `Result` track because records are created as soon as the object meets the minimum time requirement, rather than when the object leaves the scene.
`AlertWithSource` | The same as the `Alert` track, but each record also includes the source frame.

To see an example record, use the action GetExampleRecord.

Copyright 2023 Open Text
Version 24.1 | Last updated December 2023

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Product: IDOL Media Server 24.1

Topic Title: Persistent Change Detection