Mixed reality gesture based interaction for immersive analytics

用于沉浸式分析的基于混合现实手势的交互

• 批准号: 507279-2016
• 负责人: Maurer, Frank
• 金额: $ 1.82万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=610319
• 关键词: Mixed; reality; gesture; based; interaction

NOVA Chemicals has a need to understanding and exploring vast amounts of multi-dimensional (engineering and product quality) data to make better decisions and improve their chemical processes. Understanding the data is an immense problem, requiring advanced statistics & machine learning as well as visualization to bring humans into the decision making loop. The data sets are multi-dimensional in nature and often require a reduction of the dimensionality to two before a visual representation can be created. The project goal is to investigate if immersive approaches (augmented reality, mixed reality, virtual reality) to visualize and interact with these data sets can enhance data exploration and understanding. Immersive analytics visualization tools would be coupled with variable reduction techniques such as Principle Components Analysis, Partial Least Squares and Multi-way Partial Least Squares, to identify interesting high-dimensional patterns in the data as a first step in leveraging this information to improve NOVA products and its manufacturing efficiency. Concretely, we will investigate if gesture interactions can be used effectively to interact with chemical process data and if the field of view of immersive devices has an impact on human task performance.

NOVA Chemicals需要了解和探索大量多维（工程和产品质量）数据，以做出更好的决策并改进其化学工艺。理解数据是一个巨大的问题，需要先进的统计和机器学习以及可视化将人类带入决策循环。数据集本质上是多维的，并且在可以创建视觉表示之前通常需要将维度减少到两个。该项目的目标是调查沉浸式方法（增强现实，混合现实，虚拟现实）可视化和与这些数据集交互是否可以增强数据探索和理解。沉浸式分析可视化工具将与主成分分析、偏最小二乘和多向偏最小二乘等变量约简技术相结合，以识别数据中有趣的高维模式，作为利用这些信息改进NOVA产品及其制造效率的第一步。具体来说，我们将调查手势交互是否可以有效地用于与化学过程数据进行交互，以及沉浸式设备的视野是否对人类任务性能产生影响。