Reconstructed Slides: AI Red Teaming Agent: Azure AI Foundry — Nagkumar Arkalgud & Keiji Kanazawa, Microsoft

Source Video

AI Red Teaming Agent: Azure AI Foundry — Nagkumar Arkalgud & Keiji Kanazawa, Microsoft

Method

This deck is reconstructed from the existing video frame captures by detecting likely slide regions with OpenCV, cropping/upscaling those regions, deduplicating similar crops, and OCRing the cropped slide images locally. It is a cleaner companion to the full-stage frame deck.

Reconstructed Slides

• Source frame: slide-001.jpg
• Crop: full [0, 0, 960, 540] score 160.14

• Source frame: slide-002.jpg
• Crop: full [0, 0, 960, 540] score 166.55

• Source frame: slide-003.jpg
• Crop: full [0, 0, 960, 540] score 176.62

• Source frame: slide-004.jpg
• Crop: full [0, 0, 960, 540] score 175.9

• Source frame: slide-005.jpg
• Crop: full [0, 0, 960, 540] score 176.24

• Source frame: slide-006.jpg
• Crop: full [0, 0, 960, 540] score 159.05

• Source frame: slide-007.jpg
• Crop: full [0, 0, 960, 540] score 158.58

• Source frame: slide-008.jpg
• Crop: full [0, 0, 960, 540] score 158.22

• Source frame: slide-009.jpg
• Crop: full [0, 0, 960, 540] score 161.2

Dense Scene-Detected Slide Candidates

• youtube JhJKgRAmfIU dense slides