SEIDEN: Revisiting Query Processing in Video Database Systems
SEIDEN: Revisiting Query Processing in Video Database Systems
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DOI：
10.14778/3598581.3598599
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发表时间：
2023-05
期刊：
影响因子：
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通讯作者：
J. Bang;Gaurav Tarlok Kakkar;Pramod Chunduri;Subrata Mitra;Joy Arulraj
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作者：
J. Bang;Gaurav Tarlok Kakkar;Pramod Chunduri;Subrata Mitra;Joy Arulraj
最先进的视频数据库管理系统（VDBMS）通常使用轻量级代理模型来加速对象检索和聚合查询。这些系统背后的关键假设是代理模型比重量级Oracle模型快一个数量级。然而，计算机视觉的最新进展使这一假设无效。最近提出的Oracle模型的推理时间与最先进的（SoTA）VDBMS中使用的代理模型相当，甚至更低。本文介绍了Seiden，一个VDBMS，它利用了Oracle和代理模型之间的运行时差距的根本转变。Seiden不依赖于代理模型，而是直接在帧的子集上应用oracle模型来构建与查询无关的索引，并在查询处理期间使用探索-开发方案对其他帧进行采样以回答查询。通过利用视频的时间连续性和采样帧上的oracle模型的输出，Seiden提供了比SoTA VDBMS更快的查询处理和更好的查询准确性。我们的实证评估表明，在不同的查询和数据集上，Seiden平均比SoTA VDBMS快6.6倍。
State-of-the-art video database management systems (VDBMSs) often use lightweight proxy models to accelerate object retrieval and aggregate queries. The key assumption underlying these systems is that the proxy model is an order of magnitude faster than the heavyweight oracle model. However, recent advances in computer vision have invalidated this assumption. Inference time of recently proposed oracle models is on par with or even lower than the proxy models used in state-of-the-art (SoTA) VDBMSs. This paper presents Seiden, a VDBMS that leverages this radical shift in the runtime gap between the oracle and proxy models. Instead of relying on a proxy model, Seiden directly applies the oracle model over a subset of frames to build a query-agnostic index, and samples additional frames to answer the query using an exploration-exploitation scheme during query processing. By leveraging the temporal continuity of the video and the output of the oracle model on the sampled frames, Seiden delivers faster query processing and better query accuracy than SoTA VDBMSs. Our empirical evaluation shows that Seiden is on average 6.6 x faster than SoTA VDBMSs across diverse queries and datasets.