arXiv cs.AI· Yiwen Huang, Suresh Raja Neethirajan·· 15 小时前AI 评分21
DairySocialTwin：审计奶牛社交网络视频到图证据链的框架
DairySocialTwin: Auditing the video-to-graph evidence chain in cattle social networks
AI 导读
DairySocialTwin 是一个以图为中心的审计框架，用于检验视频衍生的奶牛社交图在检测、跟踪、分类与聚合环节继承的不确定性。研究基于 3 个商业奶牛场的 203 段视频（122 小时 23 分钟、15 个视角），从 839 个候选片段中保留 447 个，其中 400 个进入冻结源片段索引。
正文 · 原文
Abstract:Video-derived social graphs can appear precise while inheriting uncertainty from detection, tracking, classification, and aggregation. We present DairySocialTwin, a graph-centered audit framework applied to 203 videos (122 h 23 min) from 15 views at three commercial dairy farms. Curation retained 447 of 839 candidate clips; 400 entered a frozen source-clip index, including 71 legacy clips with unavailable farm and time metadata. Five models were compared on a development split, with an NRI-style model retained as an exploratory trade-off between class balance and dyadic output. In a 90-min manual audit, reconciliation improved switches, fragmentation, and continuous-track duration across three gap definitions, but constrained identity capacity and inherited detector errors limited claims of identity accuracy. Matched manual and reconciled summaries showed coarse agreement and assignment sensitivity. Camera-specific semantics, observation opportunity, and identity-summary-to-video trace-back made these dependencies inspectable. DairySocialTwin supports auditable relational inference without claiming permanent identity, calibrated behavior, or biological diagnosis.
| Comments: | 28 pages, 6 figures, 4 tables |
| Subjects: | Social and Information Networks (cs.SI); Artificial Intelligence (cs.AI); Image and Video Processing (eess.IV); Quantitative Methods (q-bio.QM) |
| Cite as: | arXiv:2610.32989 [cs.SI] |
| (or arXiv:2610.32989v1 [cs.SI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.32989 arXiv-issued DOI via DataCite |
Submission history
From: Suresh Neethirajan [view email]
[v1]
Mon, 24 Aug 2026 04:11:32 UTC (1,215 KB)
来源：arXiv cs.AI · arxiv.org