BR-MoE: Budgeted Semantic Release for Privacy-Preserving Traffic Analytics
Traffic cameras support useful analysis, but their outputs can reveal private information. Replacing images with text reduces direct visual exposure. It does not place a formal bound on disclosure. The published reinforcement learning and mixture-of-experts framework refines scene descriptions through relevance, coverage, and brevity rewards. It does not account for repeated releases under a fixed privacy budget. This paper proposes budgeted semantic release as an extension of that framework. Four scene experts first process isolated video chunks. Their outputs are mapped to a fixed, bounded semantic schema. A reinforcement learning controller selects which expert summaries to release and...
| Authors | Abdolazim Rezaei |
|---|---|
| Primary category | cs.CR |
| Published | 19 October 2026 |
| Last updated at source | 19 October 2026 |
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