以减少用户与系统之间的交互次数和时间，提高系统的响应速度和处理能力，提出基于机器学习算法的舰船最优交互界面设计方法。该方法设计舰船交互界面结构和按钮交互直觉状态，利用视觉注意力划分方式对舰船交互界面布局进行优化处理，得到舰船最优交互界面，再建立舰船最优交互界面交互手势库和指令库，利用相机捕捉工作人员手势图像，将其输入到机器学习算法中识别工作人员当前手势并驱动对应指令库内手势指令，实现舰船最优交互界面交互。实验表明，本文方法设计的舰船最优交互界面较为全面和简洁，有效呈现当前舰船航行相关状态数据，同时设计的舰船最优交互界面识别交互手势较为准确，具备较强的交互能力。
To reduce the interaction frequency and time between users and the system, improve the response speed and processing capability of the system, a machine learning algorithm based optimal interaction interface design method for ships is proposed. This method designs the structure of the ship interaction interface and the intuitive state of button interaction. It optimizes the layout of the ship interaction interface using visual attention partitioning to obtain the optimal interaction interface for the ship. Then, it establishes a gesture library and instruction library for the optimal interaction interface for the ship. The camera captures the gesture image of the staff and inputs it into the machine learning algorithm to recognize the current gesture of the staff and drive the corresponding gesture instructions in the instruction library, achieving the optimal interaction interface for the ship. The experiment shows that the optimal interaction interface designed by the method in this article for ships is comprehensive and concise, effectively presenting current ship navigation related status data. At the same time, the designed optimal interaction interface for ships recognizes interaction gestures more accurately and has strong interaction capabilities.
2024,46(16): 158-161 收稿日期：2024-01-15
DOI：10.3404/j.issn.1672-7649.2024.16.026
分类号：F254.2
基金项目：江苏省教育科学“十四五”规划2021年度课题（C-c/2021/03/30）；教育部产学合作协同育人项目（220806434152838）
作者简介：李玲（1987 – ），女，硕士，讲师，研究方向为信息可视化、交互设计及视觉传达
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