An Agent-Based Intelligent HCI Information System in Mixed Reality
This work addresses user experience and security challenges in mixed reality HCI systems, presenting an incremental design improvement.
The paper tackles the problem of improving user experience and information security in mixed reality systems by designing an agent-based intelligent HCI system using collaborative information and context-aware computing. The result is a flexible system that enables multiple types of awareness, including interactive target, user-experience, and confidentiality, through strategies like context pattern analysis and scalable learning.
This paper presents a design of agent-based intelligent HCI (iHCI) system using collaborative information for MR to improve user experience and information security based on context-aware computing. In order to implement target awareness system, we propose the use of non-parameter stochastic adaptive learning and a kernel learning strategy for improving the adaptivity of the recognition. The proposed design involves the use of a context-aware computing strategy to recognize patterns for simulating human awareness and processing of stereo pattern analysis. It provides a flexible customization method for scene creation and manipulation. It also enables several types of awareness related to the interactive target, user-experience, system performance, confidentiality, and agent identification by applying several strategies, such as context pattern analysis, scalable learning, data-aware confidential computing.