Problem
Research questions and friction points this paper is trying to address.
Multimodal Video Intelligence
Law-Enforcement Body-Worn Cameras
Efficient Data Processing
OmniEye: Efficient Multimodal Forensic Video Intelligence for Law-Enforcement Body-Worn Cameras
🤖 AI Summary
OmniEye系统通过多模态基础模型处理执法记录仪的视频和音频，利用SQLite数据库存储并搜索信息，以高效支持执法培训和审查。
📝 Abstract
We introduce OmniEye, a multimodal video intelligence system for law-enforcement training and review (source code available on request to verified law-enforcement and public-safety agencies). OmniEye ingests body-worn camera footage and perceives every 30-second window jointly across video and audio with one multimodal foundation model. It then stores the model's structured output in an embedded SQLite database with BM25 full-text search. Officers can question the footage through an agent that writes structured queries, retrieves candidate windows, and re-perceives them with the model before it may cite them. The whole system runs on one 16 GB GPU with a 4-bit quantization-aware-trained model, and it also scales to full bf16 precision on a multi-GPU cluster.
Innovation
Methods, ideas, or system contributions that make the work stand out.
multimodal foundation model
SQLite database
quantization-aware-trained model
full bf16 precision
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