duplicate-event-merge

To merge duplicate video event candidates, you need to consolidate events sharing the same camera, event type, ROI, related tracks, or overlapping time window. This process reduces redundancy and ensures a cleaner, more accurate event log for analysis.

Consolidating overlapping video events involves merging candidates with shared attributes like time windows and related tracks. Using a dedicated event merging process after initial detection ensures canonical events and duplicate mappings are accurately maintained.

Yes, you should use an event-rule-engine before merging duplicate video events. Processing candidates through the engine first ensures accurate canonical events and duplicate mappings, making the subsequent merging step reliable and effective.

Duplicate detection handles video events with overlapping time windows by identifying candidates that share the same camera, event type, ROI, or related tracks. It then merges these overlapping candidates to prevent redundant entries in your event log.

Yes, you can use duplicate event merging for video event analysis that involves confidence scoring. The merging process requires handling event candidate data and confidence scoring to accurately consolidate duplicates and improve overall event analysis.