Semantic Fast-Forwarding for Video Training Set Construction

Semantic Fast-Forwarding for Video Training Set Construction
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视频训练集构建的语义快进

DOI:
10.1145/3572864.3580331
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发表时间:
2023
期刊:
HotMobile '23: Proceedings of the 24th International Workshop on Mobile Computing Systems and Applications
影响因子:
--
通讯作者:
Satyanarayanan, Mahadev
Satyanarayanan, Mahadev
中科院分区:
--
文献类型:
--
作者:
Feng, Ziqiang;Satyanarayanan, Mahadev

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我们引入了视频流语义快速转发的概念,用于有效标记活动识别的训练数据。我们表明,这一概念可以通过将单个帧内的深度学习与检测到的对象的空间和时间实体关系推理相结合来实现。我们描述了一个原型,实现了这一概念,并提出了初步的实验结果,其可行性和价值。
We introduce the concept ofsemantic fast-forwardingof video streams for efficient labeling of training data for activity recognition. We show that this concept can be realized by combining deep learning within individual frames, with spatial and temporal entity-relationship reasoning about detected objects. We describe a prototype that implements this concept, and present preliminary experimental results on its feasibility and value.
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