TY -的A2 -棕褐色,振华盟——江Yujian AU -杨,雪盟——刘井宇盟——张Junming PY - 2021 DA - 2021/11/01 TI -一个轻量级的层次模型与框架水准仪关节自适应图像卷积Skeleton-Based行动识别SP - 2290304六世- 2021 AB - Skeleton-Based人类行为识别方法,人类行为可以通过时间和空间分析人类骨骼的变化。骨骼不受限于服装变化,照明条件下,或复杂的背景。这种识别方法是健壮和已引起极大的兴趣;然而,许多现有的研究与大量的深层网络使用必需的参数,提高模型的性能,从而失去了更少的计算框架数据的优势。很难先前建立模型部署到实际的应用程序基于低成本的嵌入式设备。获得较少的参数和模型更高的精度,本研究设计了一个轻量级的框架水准仪关节自适应图像卷积网络(FLAGCN)模型来解决skeleton-based行动识别任务。与经典2 s-agcn模型相比,新模型获得了更高的精度与参数的1/8和1/9的浮点操作(失败)。我们建议网络正是三个主要的改进。首先,前一个feature-fusion方法取代了多流道网络,减少所需的参数的数量。第二,在空间层面,两种图像卷积方法捕捉人类行为的不同方面的信息。 A frame-level graph convolution constructs a human topological structure for each data frame, whereas an adjacency graph convolution captures the characteristics of the adjacent joints. Third, the model proposed in this study hierarchically extracts different levels of action sequence features, making the model clear and easy to understand; further, it reduces the depth of the model and the number of parameters. A large number of experiments on the NTU RGB + D 60 and 120 data sets show that this method has the advantages of few required parameters, low computational costs, and fast speeds. It also has a simple structure and training process that make it easy to deploy in real-time recognition systems based on low-cost embedded devices. SN - 1939-0114 UR - https://doi.org/10.1155/2021/2290304 DO - 10.1155/2021/2290304 JF - Security and Communication Networks PB - Hindawi KW - ER -