The author describes building a surveillance video analysis system using Codex and GPT-luna-5.6 to process 20+ hours of footage, extracting frames, filtering static frames, creating 16-frame grids, and using natural language prompts to identify suspicious activity, with resume capability.
The paper presents a unified, high‑performance frame‑extraction framework that dynamically selects CPU or GPU decoding, leverages multithreaded and CUDA‑accelerated pipelines, keeps frames in memory, and achieves up to ten‑fold latency reductions for diverse AI video‑inference tasks.
The Hulu Brothers’ competition solution tackles large‑scale video copyright detection by extracting I‑frames, encoding them with ResNet‑18 CNN features, performing approximate nearest‑neighbor search and ORB re‑ranking to match queries to reference videos, then linearly interpolating frame correspondences for precise temporal alignment, achieving high precision, recall and F1 scores.
