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Smoking Action Recognition Based on Spatial-Temporal Convolutional Neural Networks

机译:基于时空卷积神经网络的吸烟行为识别

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摘要

In this work, we propose a system that can recognize smoking action. It utilizes data balancing and data augmentation based on GoogLeNet and Temporal segment networks architecture to achieve effective smoking action recognition. The experimental results show that the smoking accuracy rate can reach 100% for Hmdb51 test dataset. For additional irrelevant movie smoking clips, the accuracy can also be as high as 91.67%.
机译:在这项工作中,我们提出了一个可以识别吸烟行动的系统。它利用基于Googlenet和时间段网络架构的数据平衡和数据增强,以实现有效的吸烟动作识别。实验结果表明,对于HMDB51测试数据集,吸烟精度率可以达到100 \%。对于额外的无关电影吸烟夹,准确性也可以高达91.67 \%。

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