With the growth of building monitoring network, increasing human resource and funds have been invested into building monitoring system. Computer vision technology has been widely used in image recognition recently, and this technology has also been gradually applied to action recognition. There are still many disadvantages of traditional monitoring system. In this paper, a human activity recognition system which based on the convolution neural network is proposed. Using the 3D convolution neural network and the transfer learning technology, the human activity recognition engine is constructed. The Spring MVC framework is used to build the server end, and the system page is designed in HBuilder. The system not only enhances efficiency and functionality of building monitoring system, but also improves the level of building safety.
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机译：随着建筑监控网络的发展，越来越多的人力资源和资金投入到建筑监控系统中。最近，计算机视觉技术已广泛用于图像识别，并且该技术也已逐渐应用于动作识别。传统监控系统仍然存在许多弊端。本文提出了一种基于卷积神经网络的人类活动识别系统。使用3D卷积神经网络和转移学习技术，构建了人类活动识别引擎。 Spring MVC框架用于构建服务器端，系统页面在HBuilder中设计。该系统不仅提高了建筑物监控系统的效率和功能，而且提高了建筑物的安全水平。
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