Hi eMAM IT,
Greetings & Welcome to the Microsoft Q&A forum! Thank you for sharing your query.
It looks like Azure Video Indexer is misidentifying different people as the same individual in its facial recognition results. This could be due to model limitations, low-quality frames, or similarities in facial features under certain conditions. Here are some steps to improve accuracy:
- Use the Insights tab in Video Indexer to manually separate wrongly identified faces.
- Analyze the JSON insights and adjust the threshold to exclude low-confidence matches.
- Manually add more diverse and clear images of the correct individuals if you have access.
- Ensure the input video meets the recommended criteria (e.g., 30 FPS, proper lighting, and avoiding too many people per frame).
- Ensure the detected individuals appear in the frame with a clear, unobstructed view of their face and clothing.
For more information: Get observed people detection and matched faces insights
I hope this information helps.